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@InProceedings{Dudek2000,
  author       = {Dudek, Gregory and Jugessur, Deeptiman},
  title        = {Robust place recognition using local appearance based methods},
  booktitle    = {Robotics and Automation, 2000. Proceedings. ICRA'00. IEEE International Conference on},
  year         = {2000},
  volume       = {2},
  pages        = {1030--1035},
  organization = {IEEE},
  crossref     = {@inproceedings{engel2013semi, title={Semi-dense visual odometry for a monocular camera}, author={Engel, Jakob and Sturm, Jurgen and Cremers, Daniel}, booktitle={Proceedings of the IEEE international conference on computer vision}, pages={1449--1456}, year={2013} }},
  owner        = {zero},
  timestamp    = {2015.04.22},
}

@Article{Endres2014,
  author         = {Endres, Felix and Hess, Juergen and Sturm, Juergen and Cremers, Daniel and Burgard, Wolfram},
  title          = {3-D Mapping With an RGB-D Camera},
  journal        = {IEEE Transactions on Robotics},
  year           = {2014},
  volume         = {30},
  number         = {1},
  pages          = {177--187},
  __markedentry  = {[x:]},
  comment        = {Rgb-d SLAM经典作品，Endres大大的，2012年的icra上已发过一次。},
  crossref       = {@inproceedings{engel2013semi, title={Semi-dense visual odometry for a monocular camera}, author={Engel, Jakob and Sturm, Jurgen and Cremers, Daniel}, booktitle={Proceedings of the IEEE international conference on computer vision}, pages={1449--1456}, year={2013} }},
  file           = {Published version:Endres2014.pdf:PDF},
  keywords       = {rgb-d slam, graph-based slam, important, rank5, qualityAssured},
  owner          = {GaoXiang},
  timestamp      = {2014.04.19},
}

@Article{Adams2014,
  author         = {Adams, M. and Vo, B.-N. and Mahler, R. and Mullane, J.VOV},
  title          = {SLAM Gets a PHD: New Concepts in Map Estimation},
  journal        = {IEEE Robotics Automation Magazine},
  year           = {2014},
  volume         = {21},
  number         = {2},
  pages          = {26--37},
  issn           = {1070-9932},
  __markedentry  = {[y:3]},
  comment        = {使用PHD作为基本理论的SLAM，比较有新意，且是该方向经典的工作，直接继承�??????????2013年的RFS理论。},
  file           = {Published version:Adams2014.pdf:PDF},
  keywords       = {rfs, phd, important, rank4, qualityAssured},
  owner          = {y},
  timestamp      = {2014.08.24},
}

@Article{Agarwal2014,
  author =         {Agarwal, P. and Burgard, W. and Stachniss, C.},
  title =          {Survey of Geodetic Mapping Methods: Geodetic Approaches to Mapping and the Relationship to Graph-Based SLAM},
  journal =        {Robotics Automation Magazine, IEEE},
  year =           {2014},
  volume =         {21},
  number =         {3},
  pages =          {63-80},
  month =          {Sept},
  doi =            {10.1109/MRA.2014.2322282},
  file =           {Agarwal2014.pdf:Agarwal2014.pdf:PDF},
  issn =           {1070-9932},
  keywords =       {SLAM (robots), cartography, mobile robots, path planning, geodetic approach, geodetic mapping methods, graph-based SLAM, large-scale mapping process, map building, robot localization, simultaneous localization and mapping, Mapping, Mobile robots, Poles and towers, Simultaneous localization and mapping, Sparse matrices, qualityAssured, rank4},
  owner =          {x},
  timestamp =      {2015.10.16}
}

@InCollection{Agrawal2008,
  author         = {Agrawal, Motilal and Konolige, Kurt and Blas, MortenRufus},
  title          = {CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching},
  booktitle      = {Computer Vision--ECCV 2008},
  publisher      = {Springer Berlin Heidelberg},
  year           = {2008},
  editor         = {Forsyth, David and Torr, Philip and Zisserman, Andrew},
  volume         = {5305},
  series         = {Lecture Notes in Computer Science},
  pages          = {102--115},
  isbn           = {978-3-540-88692-1},
  comment        = {提出FAST特征的文章，写到fast特征�一般要引用本文。},
  file           = {Published version:Agrawal2008.pdf:PDF},
  keywords       = {rank1, qualityAssured},
  language       = {English},
  owner          = {y},
  timestamp      = {2014.08.28},
}

@Article{Aldoma2012,
  author    = {Aldoma, Aitor and Marton, Zoltan-Csaba and Tombari, Federico and Wohlkinger, Walter and Potthast, Christian and Zeisl, Bernhard and Rusu, Radu Bogdan and Gedikli, Suat and Vincze, Markus},
  title     = {Point Cloud Library},
  journal   = {IEEE Robotics \& Automation Magazine},
  year      = {2012},
  volume    = {1070},
  number    = {9932/12},
  comment   = {PCL},
  owner     = {x},
  timestamp = {2014.12.09},
}

@Article{An2012,
  Title                    = {Line Segment-Based Indoor Mapping with Salient Line Feature Extraction},
  Author                   = {An, S. Y. and Kang, J. G. and Lee, L. K. and Oh, S. Y.},
  Journal                  = {Advanced Robotics},
  Year                     = {2012},
  Number                   = {5-6},
  Pages                    = {437--460},
  Volume                   = {26},

  File                     = {An2012.pdf:An2012.pdf:PDF},
  ISSN                     = {0169-1864},
  Keywords                 = {RBPF-SLAM line segment scan point clustering iterative end point fitting line association mobile robot slam representation algorithms},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Anand2012,
  author =         {Anand, Abhishek and Koppula, Hema Swetha and Joachims, Thorsten and Saxena, Ashutosh},
  title =          {Contextually guided semantic labeling and search for three-dimensional point clouds},
  journal =        {The International Journal of Robotics Research},
  year =           {2012},
  pages =          {0278364912461538},
  __markedentry =  {[x:]},
  file =           {Anand2012.pdf:Anand2012.pdf:PDF},
  keywords =       {qualityAssured, rank5},
  owner =          {x},
  publisher =      {SAGE Publications},
  timestamp =      {2015.05.30}
}

@Article{Arbelaez2011,
  Title                    = {Contour detection and hierarchical image segmentation},
  Author                   = {Arbelaez, Pablo and Maire, Michael and Fowlkes, Charless and Malik, Jitendra},
  Journal                  = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  Year                     = {2011},
  Number                   = {5},
  Pages                    = {898--916},
  Volume                   = {33},

  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.05.30}
}

@Article{Arth2015,
  author =         {Arth, C. and Pirchheim, C. and Ventura, J. and Schmalstieg, D. and Lepetit, V.},
  title =          {Instant Outdoor Localization and SLAM Initialization from 2.5D Maps},
  journal =        {Visualization and Computer Graphics, IEEE Transactions on},
  year =           {2015},
  volume =         {21},
  number =         {11},
  pages =          {1309-1318},
  month =          {Nov},
  doi =            {10.1109/TVCG.2015.2459772},
  file =           {Arth2015.pdf:Arth2015.pdf:PDF},
  issn =           {1077-2626},
  keywords =       {Buildings, Cameras, Image segmentation, Mobile handsets, Simultaneous localization and mapping, Solid modeling, Three-dimensional displays, 2D map, SLAM, geo-localization, image registration, outdoor augmented reality, qualityAssured, rank1},
  owner =          {x},
  timestamp =      {2015.10.16}
}

@InProceedings{Arthur2007,
  author       = {Arthur, David and Vassilvitskii, Sergei},
  title        = {K-means++: The advantages of careful seeding},
  booktitle    = {Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms},
  year         = {2007},
  pages        = {1027--1035},
  organization = {Society for Industrial and Applied Mathematics},
  owner        = {cyang},
  timestamp    = {2016.10.01},
}

@Article{Artieda2009,
  author    = {Artieda, Jorge and Sebastian, Jos{\'e} M and Campoy, Pascual and Correa, Juan F and Mondrag{\'o}n, Iv{\'a}n F and Mart{\'\i}nez, Carol and Olivares, Miguel},
  title     = {Visual 3-d slam from uavs},
  journal   = {Journal of Intelligent and Robotic Systems},
  year      = {2009},
  volume    = {55},
  number    = {4-5},
  pages     = {299--321},
  comment   = {SLAM在UAV里的应用},
  owner     = {x},
  publisher = {Springer},
  timestamp = {2015.05.17},
}

@Article{Arun1987,
  author         = {Arun, K Somani and Huang, Thomas S and Blostein, Steven D},
  title          = {Least-squares fitting of two 3-D point sets},
  journal        = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  year           = {1987},
  number         = {5},
  pages          = {698--700},
  comment        = {ICP初始文章。写ICP时引用�?�},
  keywords       = {rank1, qualityAssured},
  owner          = {x},
  publisher      = {IEEE},
  timestamp      = {2014.09.28},
}

@Article{Bacca2013,
  Title                    = {Long-term mapping and localization using feature stability histograms},
  Author                   = {B. Bacca and J. Salvi and X. Cuf{\'{\i}}},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2013},
  Number                   = {12},
  Pages                    = {1539--1558},
  Volume                   = {61},

  Abstract                 = {Abstract This work proposes a system for long-term mapping and localization based on the Feature Stability Histogram (FSH) model which is an innovative feature management approach able to cope with changing environments. \{FSH\} is built using a voting schema, where re-observed features are promoted; otherwise the feature progressively decreases its corresponding \{FSH\} value. \{FSH\} is inspired by the human memory model. This model introduces concepts of Short-Term Memory (STM), which retains information long enough to use it, and Long-Term Memory (LTM), which retains information for longer periods of time. If the entries in \{STM\} are continuously rehearsed, they become part of LTM. However, this work proposes a change in the pipeline of this model, allowing any feature to be part of \{STM\} or \{LTM\} depending on the feature strength. \{FSH\} stores the stability values of local features, stable features are only used for localization and mapping. Experimental validation of the \{FSH\} model was conducted using the FastSLAM framework and a long-term dataset collected during a period of one year at different environmental conditions. The experiments carried out include qualitative and quantitative results such as: filtering out dynamic objects, increasing map accuracy, scalability, and reducing the data association effort in long-term runs. },
  File                     = {Published version:Bacca2013.pdf:PDF},
  ISSN                     = {0921-8890},
  Keywords                 = {Long-term localization and mapping},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Bachrach2012,
  author         = {Bachrach, Abraham and Prentice, Samuel and He, Ruijie and Henry, Peter and Huang, Albert S and Krainin, Michael and Maturana, Daniel and Fox, Dieter and Roy, Nicholas},
  title          = {Estimation, planning, and mapping for autonomous flight using an RGB-D camera in GPS-denied environments},
  journal        = {The International Journal of Robotics Research},
  year           = {2012},
  volume         = {31},
  number         = {11},
  pages          = {1320--1343},
  __markedentry  = {[y:5]},
  comment        = {大�?�全，从SLAM到Planning的所有东西都提到了�?? 用了Fast特征点，金字塔提取�?? IJRR上的都是这种巨大的文章么�???????????? -从现在看过的而言确实是啊。顶楼主。},
  file           = {Published version:Bachrach2012.pdf:PDF},
  keywords       = {rgb-d slam, planning, important, rank3, qualityAssured},
  owner          = {y},
  publisher      = {Sage Publications},
  timestamp      = {2014.06.11},
}

@Article{Balzer2013,
  Title                    = {CLAM: Coupled Localization and Mapping with Efficient Outlier Handling},
  Author                   = {Balzer, J. and Soatto, S.},
  Journal                  = {2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  Year                     = {2013},
  Pages                    = {1554--61},

  File                     = {Published version:Balzer2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Misc{Barfoot2016,
  author    = {Barfoot, TD},
  title     = {State Estimation for Robotics: A Matrix Lie Group Approach},
  year      = {2016},
  publisher = {Draft in preparation for publication by Cambridge University Press},
}

@Article{Barkby2012,
  Title                    = {Bathymetric particle filter SLAM using trajectory maps},
  Author                   = {Barkby, S. and Williams, S. B. and Pizarro, O. and Jakuba, M. V.},
  Journal                  = {International Journal of Robotics Research},
  Year                     = {2012},
  Note                     = {Times Cited: 5 Barkby, Stephen Williams, Stefan B. Pizarro, Oscar Jakuba, Michael V. 5 Si},
  Number                   = {12},
  Pages                    = {1409--1430},
  Volume                   = {31},

  Doi                      = {10.1177/0278364912459666},
  ISSN                     = {0278-3649},
  Keywords                 = {SLAM mapping navigation bathymetry Gaussian process RBPF vehicles},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article},
  Url                      = {<Go to ISI>://WOS:000311643300005}
}

@Article{Bastien2012,
  Title                    = {Theano: new features and speed improvements},
  Author                   = {Bastien, Fr{\'e}d{\'e}ric and Lamblin, Pascal and Pascanu, Razvan and Bergstra, James and Goodfellow, Ian and Bergeron, Arnaud and Bouchard, Nicolas and Warde-Farley, David and Bengio, Yoshua},
  Journal                  = {arXiv preprint arXiv:1211.5590},
  Year                     = {2012},

  Owner                    = {zero},
  Timestamp                = {2015.04.12}
}

@InCollection{Bay2006,
  author         = {Bay, Herbert and Tuytelaars, Tinne and Van Gool, Luc},
  title          = {Surf: Speeded up robust features},
  booktitle      = {Computer Vision--ECCV 2006},
  publisher      = {Springer},
  year           = {2006},
  pages          = {404--417},
  comment        = {提出surf的文章�?�},
  keywords       = {SURF, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.09.30},
}

@Article{Beeson2010,
  author         = {Beeson, P. and Modayil, J. and Kuipers, B.},
  title          = {Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy},
  journal        = {International Journal of Robotics Research},
  year           = {2010},
  volume         = {29},
  number         = {4},
  pages          = {428--459},
  issn           = {0278-3649},
  comment        = {14.10.26 极其牛叉的一篇文章�?�讲述了建图的方方面面，综述写的十分精彩�? 整篇长文是围绕HSSH（Hybrid Spatial Semantic Hierachy）展�?的，其核心�?�想是，�?部地图用Metric表示，全�?地图用拓扑表示�?�Metric表示比较精确，可以用于准确的定点与导航，但是范围小，容易出现累积误差。拓扑地图则对于距离误差不敏感，适合表示大范围的地图。对于拓扑地图，该文使用了一套完整的符号，包括Path, Region, Place, Gateway。简单地说，地图是由若干个Region通过Gateway连接起来的东西�?�},
  file           = {Beeson2010.pdf:pdf/Beeson2010.pdf:PDF},
  keywords       = {mapping localization autonomous agents cognitive robotics topological maps localization representation environments complexity inference space slam, rank5, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Benedettelli2012,
  author         = {Benedettelli, D. and Garulli, A. and Giannitrapani, A.},
  title          = {Cooperative SLAM using M-Space representation of linear features},
  journal        = {Robotics and Autonomous Systems},
  year           = {2012},
  volume         = {60},
  number         = {10},
  pages          = {1267--1278},
  issn           = {0921-8890},
  comment        = {14.10.27 只看了摘要�?? 讲多机器人SLAM的文章�?? 分为三步�????????????1.各机器人独立进行SLAM，生成独立的地图�????????????2.当机器人相遇（meet）时，合并子图；3.之后的SLAM过程在合并之后的地图上进行�?? 个人猜测：多机器人的相对位姿的配准时机比较讲究，不能随时随地就配。所以要设计出这么一套机制�?�},
  keywords       = {SLAM Mapping Multi-robot M-Space simultaneous localization environments, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Bengio2013,
  author         = {Bengio, Yoshua and Courville, Aaron and Vincent, Pascal},
  title          = {Representation learning: A review and new perspectives},
  journal        = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year           = {2013},
  volume         = {35},
  number         = {8},
  pages          = {1798--1828},
  comment        = {15.1.13 和bengio以往的作品差不多，讲关于dl各种算法的发展进度和应用�????????????30多页的一篇综述�?? 写得非常全面，在引用dl文献时可参照这篇文章去引。},
  file           = {Bengio2013.pdf:Bengio2013.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {x},
  publisher      = {IEEE},
  timestamp      = {2014.12.17},
}

@Article{Bentley1975,
  author    = {Bentley, Jon Louis},
  title     = {Multidimensional binary search trees used for associative searching},
  journal   = {Communications of the ACM},
  year      = {1975},
  volume    = {18},
  number    = {9},
  pages     = {509--517},
  owner     = {cyang},
  publisher = {ACM},
  timestamp = {2016.10.02},
}

@InProceedings{Bergstra2010,
  author    = {Bergstra, James and Breuleux, Olivier and Bastien, Fr{\'{e}}d{\'{e}}ric and Lamblin, Pascal and Pascanu, Razvan and Desjardins, Guillaume and Turian, Joseph and Warde-Farley, David and Bengio, Yoshua},
  title     = {Theano: a {CPU} and {GPU} Math Expression Compiler},
  booktitle = {Proceedings of the Python for Scientific Computing Conference ({SciPy})},
  year      = {2010},
  month     = {\#jun\#},
  note      = {Oral Presentation},
  abstract  = {Theano is a compiler for mathematical expressions in Python that combines the convenience of NumPy’s syntax with the speed of optimized native machine language. The user composes mathematical expressions in a high-level description that mimics NumPy’s syntax and semantics, while being statically typed and functional (as opposed to imperative). These expressions allow Theano to provide symbolic differentiation. Before performing computation, Theano optimizes the choice of expressions, translates them into C++ (or CUDA for GPU), compiles them into dynamically loaded Python modules, all automatically. Common machine learning algorithms implemented with Theano are from 1.6�???????????? to 7.5�???????????? faster than competitive alternatives (including those implemented with C/C++, NumPy/SciPy and MATLAB) when compiled for the CPU and between 6.5�???????????? and 44�???????????? faster when compiled for the GPU. This paper illustrates how to use Theano, outlines the scope of the compiler, provides benchmarks on both CPU and GPU processors, and explains its overall design.},
  comment   = {theano},
  location  = {Austin, TX},
  owner     = {x},
  timestamp = {2015.01.05},
}

@InProceedings{Birem2014,
  Title                    = {SAIL-MAP: Loop-closure detection using saliency-based features},
  Author                   = {Birem, Merwan and Quinton, Jean-Charles and Berry, Francois and Mezouar, Youcef},
  Booktitle                = {Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on},
  Year                     = {2014},
  Organization             = {IEEE},
  Pages                    = {4543--4548},

  Owner                    = {x},
  Timestamp                = {2015.01.01}
}

@Article{Biswas2013,
  Title                    = {Localization and navigation of the CoBots over long-term deployments},
  Author                   = {Biswas, Joydeep and Veloso, Manuela M.},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1679--1694},
  Volume                   = {32},

  Abstract                 = {For the last three years, we have developed and researched multiple collaborative robots, CoBots, which have been autonomously traversing our multi-floor buildings. We pursue the goal of long-term autonomy for indoor service mobile robots as the ability for them to be deployed indefinitely while they perform tasks in an evolving environment. The CoBots include several levels of autonomy, and in this paper we focus on their localization and navigation algorithms. We present the Corrective Gradient Refinement (CGR) algorithm, which refines the proposal distribution of the particle filter used for localization with sensor observations using analytically computed state space derivatives on a vector map. We also present the Fast Sampling Plane Filtering algorithm that extracts planar regions from depth images in real time. These planar regions are then projected onto the 2D vector map of the building, and along with the laser rangefinder observations, used with CGR for localization. For navigation, we present a hierarchical planner, which computes a topological policy using a graph representation of the environment, computes motion commands based on the topological policy, and then modifies the motion commands to side-step perceived obstacles. We started logging the deployments of the CoBots one and a half years ago, and have since collected logs of the CoBots traversing more than 130 km over 1082 deployments and a total run time of 182 h, which we publish as a dataset consisting of more than 10 million laser scans. The logs show that although there have been continuous changes in the environment, the robots are robust to most of them, and there exist only a few locations where changes in the environment cause increased uncertainty in localization.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1679},
  File                     = {Published version:Biswas2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Blanco2013,
  Title                    = {A robust, multi-hypothesis approach to matching occupancy grid maps},
  Author                   = {Blanco, J. L. and Gonzalez-Jimenez, J. and Fernandez-Madrigal, J. A.},
  Journal                  = {Robotica},
  Year                     = {2013},
  Pages                    = {687--701},
  Volume                   = {31},

  ISSN                     = {0263-5747},
  Keywords                 = {Mobile robots SLAM Robot localization Pose estimation and registration navigation metric-topological slam image registration local descriptors representation environments consensus robots},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Bo2014,
  author         = {Bo, Liefeng and Ren, Xiaofeng and Fox, Dieter},
  title          = {Learning hierarchical sparse features for RGB-D object recognition},
  journal        = {International Journal of Robotics Research},
  year           = {2014},
  volume         = {33},
  number         = {4},
  pages          = {581--599},
  __markedentry  = {[x:]},
  comment        = {14.11.18 用层次化�????????????疏编码（怎么�????????????么都可以层次化）来学习RGBD数据中的特征。用到了R,G,B,I,D和法线共八维的向量�?? 方法是先用K-SVD学习字典，然后用OMP（正交追踪）计算在当前字典下的编码�?�我觉得该工作也可以用于Loop Closure Dection中�?? 优点：学习字典与线�?�变换，计算量相对较小�?? 缺点：线性方法有�????????????限�?�；把图像分成batches可能丢失了batch之间的结构信息�?? 15.1.13 这篇文章值得细读�????????????读�?�},
  file           = {Published version:Bo2014.pdf:PDF},
  keywords       = {object recognition, feature, sparse coding, Feature learning, rank5, qualityAssured},
  owner          = {y},
  publisher      = {SAGE Publications},
  timestamp      = {2014.08.24},
}

@Article{Boal2014,
  author    = {Boal,Jaime and S{\'{a}}nchez-Miralles,{\'{A}}lvaro and Arranz,{\'{A}}lvaro},
  title     = {Topological simultaneous localization and mapping: a survey},
  journal   = {Robotica},
  year      = {2014},
  volume    = {32},
  pages     = {803--821},
  abstract  = {ABSTRACT SUMMARY One of the main challenges in robotics is navigating autonomously through large, unknown, and unstructured environments. Simultaneous localization and mapping (SLAM) is currently regarded as a viable solution for this problem. As the traditional metric approach to SLAM is experiencing computational difficulties when exploring large areas, increasing attention is being paid to topological SLAM, which is bound to provide sufficiently accurate location estimates, while being significantly less computationally demanding. This paper intends to provide an introductory overview of the most prominent techniques that have been applied to topological SLAM in terms of feature detection, map matching, and map fusion.},
  file      = {Boal2014.pdf:Boal2014.pdf:PDF},
  issn      = {1469-8668},
  issue     = {05},
  numpages  = {19},
  owner     = {y},
  timestamp = {2014.08.25},
}

@InProceedings{Bosse2003,
  Title                    = {An Atlas framework for scalable mapping},
  Author                   = {Bosse, Michael and Newman, Paul and Leonard, John and Soika, Martin and Feiten, Wendelin and Teller, Seth},
  Booktitle                = {Robotics and Automation, 2003. Proceedings. ICRA'03. IEEE International Conference on},
  Year                     = {2003},
  Organization             = {IEEE},
  Pages                    = {1899--1906},
  Volume                   = {2},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@Article{Botterill2011,
  Title                    = {Bag-of-Words-Driven, Single-Camera Simultaneous Localization and Mapping},
  Author                   = {Botterill, T. and Mills, S. and Green, R.},
  Journal                  = {Journal of Field Robotics},
  Year                     = {2011},
  Number                   = {2},
  Pages                    = {204--226},
  Volume                   = {28},

  ISSN                     = {1556-4959},
  Keywords                 = {appearance algorithm vision graphs slam map},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Botterill2013,
  Title                    = {Correcting Scale Drift by Object Recognition in Single-Camera SLAM},
  Author                   = {Botterill, Tom and Mills, Steven and Green, Richard},
  Journal                  = {IEEE Transactions On Cybernetics},
  Year                     = {2013},
  Number                   = {6SI},
  Pages                    = {1767--1780},
  Volume                   = {43},

  File                     = {Published version:Botterill2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Bourlard1988,
  Title                    = {Auto-association by multilayer perceptrons and singular value decomposition},
  Author                   = {Bourlard, Herv{\'e} and Kamp, Yves},
  Journal                  = {Biological cybernetics},
  Year                     = {1988},
  Number                   = {4-5},
  Pages                    = {291--294},
  Volume                   = {59},

  Owner                    = {zero},
  Publisher                = {Springer},
  Timestamp                = {2015.04.09}
}

@Article{Bradski2000,
  author    = {Bradski, Gary},
  title     = {The opencv library},
  journal   = {Doctor Dobbs Journal},
  year      = {2000},
  volume    = {25},
  number    = {11},
  pages     = {120--126},
  comment   = {opencv引用},
  owner     = {x},
  publisher = {M AND T PUBLISHING INC},
  timestamp = {2014.12.09},
}

@Article{Bresson2015,
  author =         {Bresson, G. and Feraud, T. and Aufrere, R. and Checchin, P. and Chapuis, R.},
  title =          {Real-Time Monocular SLAM With Low Memory Requirements},
  journal =        {Intelligent Transportation Systems, IEEE Transactions on},
  year =           {2015},
  volume =         {16},
  number =         {4},
  pages =          {1827-1839},
  month =          {Aug},
  doi =            {10.1109/TITS.2014.2376780},
  file =           {Bresson2015.pdf:Bresson2015.pdf:PDF},
  issn =           {1524-9050},
  keywords =       {Kalman filters, SLAM (robots), covariance matrices, linearisation techniques, mobile robots, position control, robot vision, 3-D uncertainty, EKF-SLAM algorithm, Kalman gain, MSLAM, corrective factor, covariance matrix, extended Kalman filter, image plane, linearization errors, linearization failures, low memory requirements, minimal Cartesian representation, monocular SLAM problem, real-time monocular SLAM, simultaneous localization and mapping techniques, unknown environment, vehicle localization, Cameras, Ellipsoids, Jacobian matrices, Kalman filters, Simultaneous localization and mapping, Uncertainty, Vehicles, Intelligent vehicles, land vehicles, robot vision systems, simultaneous localization and mapping, qualityAssured, rank2},
  owner =          {x},
  timestamp =      {2015.10.16}
}

@InProceedings{Burri2015,
  author       = {Burri, Michael and Oleynikova, Helen and Achtelik, Markus W and Siegwart, Roland},
  title        = {Real-time visual-inertial mapping, re-localization and planning onboard MAVs in unknown environments},
  booktitle    = {Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on},
  year         = {2015},
  pages        = {1872--1878},
  organization = {IEEE},
}

@Article{Cadena2012,
  author         = {Cadena, C. and Galvez-Lopez, D. and Tardos, J. D. and Neira, J.},
  title          = {Robust Place Recognition With Stereo Sequences},
  journal        = {IEEE Transactions on Robotics},
  year           = {2012},
  volume         = {28},
  number         = {4},
  pages          = {871--885},
  issn           = {1552-3098},
  comment        = {14.10.28 主题是用BoW模型做loop closure detection。在传统的BoW上面做了�????????????些改进，例如引入归一化的相似度�?�评判相似度之后做了CRF�????????????测�?? 使用surf作为图像特征�???????????? 验证工作十分完善。与FAB-MAP 2.0比较了precision和recall曲线�???????????? 15.1.13 可作为不错的参�?�文献，看看研究lc的同学都用什么指标来评价算法的�?�},
  file           = {Cadena2012.pdf:pdf/Cadena2012.pdf:PDF},
  keywords       = {Bag of words (BoW) computer vision conditional random fields (CRFs) recognition simultaneous localization and mapping (SLAM) random-fields localization, rank4, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Cadena2014,
  author         = {Cadena, César and Košecká, Jana},
  title          = {Semantic parsing for priming object detection in indoors RGB-D scenes},
  journal        = {The International Journal of Robotics Research},
  year           = {2014},
  __markedentry  = {[x:]},
  abstract       = {The semantic mapping of the environment requires simultaneous segmentation and categorization of the acquired stream of sensory information. The existing methods typically consider the semantic mapping as the final goal and differ in the number and types of considered semantic categories. We envision semantic understanding of the environment as an on-going process and seek representations which can be refined and adapted depending on the task and robot’s interaction with the environment. In this work we propose a novel and efficient method for semantic parsing, which can be adapted to the task at hand and enables localization of objects of interest in indoor environments. For basic mobility tasks we demonstrate how to obtain initial semantic segmentation of the scene into ground, structure, furniture and props categories which constitute the first level of hierarchy. Then, we propose a simple and efficient method for predicting locations of objects that based on their size afford a manipulation task. In our experiments we use the publicly available NYU V2 dataset and obtain better or comparable results than the state of the art at a fraction of the computational cost. We show the generalization of our approach on two more publicly available datasets.},
  comment        = {cadena出品，必属精品系列。 思路是先把地图用super pixel，弄出一个生成树。然后对每一个super pixel，提取一共十五维的特征，包括外观，3D信息，用它们来分类。 事实上语义地图就是个分割-分类的问题，难点是要做到实时，并且类别设置要妥当。 本文的类别是四分类：ground, structure, furniture, props. 也就是所有的super pixel都属于这四类之一。 对于不同的任务，其对于地图的认识层次需求也是不用的。机器人只需感知有兴趣的物体，不用识别环境里所有乱七八糟的东西。 文章有代码：www.di.ens.fr/~mschmidt/Software/UGM.html dataset: NYU V2 2015.6 仔仔细细地读了一遍，代码也跑通了，虽然未细看。 核心是用CRF表示类别的分布，并推理出每个物体的标签。 流程：super pixel seg. -> image & 3d features ->graph structure -> compute potentials of CRF -> inference. 对一张普通的图需要计算20秒左右。可能是因为matlab本身慢。最花时间的是3D特征的计算，尽管论文里认为是entropy。 优点：CRF可以推理出很复杂的结构。灵活性好。 缺点：仅能对单张图进行表示，计算量仍然很大（尽管树结构能简化图的表达），整体算法较复杂。需要事先训练分类器。语义方面只有四个类别，比较单一。 最直观的应用是直接丢进SLAM里计算，这样能得到一张semantic map，真正的语义地图，虽然语义比较简单。这个在Zhao2014中已经做过了。},
  eprint         = {http://ijr.sagepub.com/content/early/2014/10/27/0278364914549488.full.pdf+html},
  file           = {Cadena2014.pdf:Cadena2014.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {x},
  timestamp      = {2015.01.01},
}

@Article{Cadena2016,
  author  = {Cesar, Cadena and Luca Carlone and Henry C. and Yasir Latif and Davide Scaramuzza and Jose Neira and Ian D Reid and John J., Leonard},
  title   = {Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age},
  journal = {arXiv preprint arXiv:1606.05830},
  year    = {2016},
  file    = {Cadena2016.pdf:Cadena2016.pdf:PDF},
}
@inproceedings{calonder2010brief,
  title={Brief: Binary robust independent elementary features},
  author={Calonder, Michael and Lepetit, Vincent and Strecha, Christoph and Fua, Pascal},
  booktitle={European conference on computer vision},
  pages={778--792},
  year={2010},
  organization={Springer}
}

@Article{Carlevaris-Bianco2014,
  author =         {Carlevaris-Bianco, N. and Kaess, M. and Eustice, R.M.},
  title =          {Generic Node Removal for Factor-Graph SLAM},
  journal =        {Robotics, IEEE Transactions on},
  year =           {2014},
  volume =         {30},
  number =         {6},
  pages =          {1371-1385},
  month =          {Dec},
  doi =            {10.1109/TRO.2014.2347571},
  file =           {Carlevaris-Bianco2014.pdf:Carlevaris-Bianco2014.pdf:PDF},
  issn =           {1552-3098},
  keywords =       {SLAM (robots), computational complexity, graph theory, mobile robots, GLC method, Kullback-Leibler divergence, computational complexity, factor-graph SLAM, generic factor-based method, generic linear constraints, generic node removal, monocular vision, simultaneous localization and mapping, Approximation methods, Correlation, Mobile robots, Optimization, Simultaneous localization and mapping, Factor-graphs, long-term autonomy, marginalization, mobile robotics, simultaneous localization and mapping (SLAM), qualityAssured, rank3},
  owner =          {x},
  timestamp =      {2015.10.16}
}

@Article{Carlone2011,
  Title                    = {Simultaneous Localization and Mapping Using {Rao-Blackwell}ized Particle Filters in Multi Robot Systems},
  Author                   = {Carlone, L. and Ng, M. K. and Du, J. J. and Bona, B. and Indri, M.},
  Journal                  = {Journal of Intelligent \& Robotic Systems},
  Year                     = {2011},
  Number                   = {2},
  Pages                    = {283--307},
  Volume                   = {63},

  ISSN                     = {0921-0296},
  Keywords                 = {Mobile robots Multi robot SLAM Rao-Blackwellized particle filters slam},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Carlone2014,
  Title                    = {From Angular Manifolds to the Integer Lattice: Guaranteed Orientation Estimation With Application to Pose Graph Optimization},
  Author                   = {Carlone, L. and Censi, A.},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2014},

  Month                    = {April},
  Number                   = {2},
  Pages                    = {475-492},
  Volume                   = {30},

  Doi                      = {10.1109/TRO.2013.2291626},
  ISSN                     = {1552-3098},
  Keywords                 = {computational complexity;concave programming;graph theory;integer programming;iterative methods;maximum likelihood estimation;probability;quadratic programming;statistical analysis;MOIE2D;angular manifolds;angular pose component;guaranteed orientation estimation;integer lattice;iterative pose graph optimization methods;iterative solvers;likelihood function;manifold product;maximum likelihood estimate;multihypothesis orientation-from-lattice estimation in 2D;node orientation;nonlinear optimization problem;nontrivial topology;precise probabilistic guarantees;unconstrained quadratic optimization problem;Manifolds;Maximum likelihood estimation;Noise;Optimization;Simultaneous localization and mapping;Integer quadratic programming;SO(2) manifold;mobile robots;multi-hypothesis estimation;orientation estimation;pose graph optimization;simultaneous localization and mapping (SLAM)},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Carrera2011,
  Title                    = {SLAM-based automatic extrinsic calibration of a multi-camera rig},
  Author                   = {Carrera, Gerardo and Angeli, Adrien and Davison, Andrew J},
  Booktitle                = {Robotics and Automation (ICRA), 2011 IEEE International Conference on},
  Year                     = {2011},
  Organization             = {IEEE},
  Pages                    = {2652--2659},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@Article{Castellanos2001,
  author               = {Castellanos, JA and Neira, J and Tardos, JD},
  title                = {Multisensor fusion for simultaneous localization and map building},
  journal              = {IEEE Transactions On Robotics And Automation},
  year                 = {2001},
  volume               = {17},
  number               = {6},
  pages                = {908--914},
  month                = {\#dec\#},
  issn                 = {{1042-296X}},
  abstract             = {This paper describes how multisensor fusion increases both reliability and precision of the environmental observations used for the simultaneous localization and map-building problem for mobile robots. Multisensor fusion is performed at the level of landmarks, which represent sets of related and possibly correlated sensor observations. The work emphasizes the idea of partial redundancy due to the different nature of the information provided by different sensors. Experimentation with a mobile robot equipped with a multisensor system composed of a 2-D laser rangefinder and a charge coupled device camera is reported.},
  comment              = {早期的sensor fusion文章。},
  file                 = {Castellanos2001.pdf:Castellanos2001.pdf:PDF},
  keywords             = {application, indoor, rank1, qualityAssured},
  orcid-numbers        = {{Tardos, Juan/0000-0002-4518-5876}},
  owner                = {x},
  researcherid-numbers = {{Tardos, Juan/F-9204-2013}},
  timestamp            = {2014.10.05},
  unique-id            = {{ISI:000173337600014}},
}

@Article{Castle2010,
  Title                    = {Combining monoSLAM with object recognition for scene augmentation using a wearable camera},
  Author                   = {Castle, R. O. and Klein, G. and Murray, D. W.},
  Journal                  = {Image And Vision Computing},
  Year                     = {2010},
  Number                   = {11},
  Pages                    = {1548--1556},
  Volume                   = {28},

  File                     = {Published version:Castle2010.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Cheein2010,
  Title                    = {SLAM algorithm applied to robotics assistance for navigation in unknown environments},
  Author                   = {Cheein, Fernando A Auat and Lopez, Natalia and Soria, Carlos M and di Sciascio, Fernando A and Pereira, F Lobo and Carelli, Ricardo},
  Journal                  = {Journal of neuroengineering and rehabilitation},
  Year                     = {2010},
  Number                   = {1},
  Pages                    = {10},
  Volume                   = {7},

  Owner                    = {x},
  Publisher                = {BioMed Central Ltd},
  Timestamp                = {2015.05.17}
}

@InProceedings{Chekhlov2007,
  author       = {Chekhlov, Denis and Gee, Andrew P and Calway, Andrew and Mayol-Cuevas, Walterio},
  title        = {Ninja on a plane: Automatic discovery of physical planes for augmented reality using visual slam},
  booktitle    = {Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality},
  year         = {2007},
  pages        = {1--4},
  organization = {IEEE Computer Society},
  comment      = {SLAM在VR里的应用},
  owner        = {x},
  timestamp    = {2015.05.17},
}

@Article{Chen2007,
  author         = {Chen, Zhenhe and Samarabandu, Jagath and Rodrigo, Ranga},
  title          = {Recent advances in simultaneous localization and map-building using computer vision},
  journal        = {Advanced Robotics},
  year           = {2007},
  volume         = {21},
  number         = {3-4},
  pages          = {233--265},
  __markedentry  = {[x:]},
  comment        = {比较经典的视觉SLAM综述，可惜比较早，后面的工作没有讲到。},
  file           = {Published version:Chen2007.pdf:PDF},
  keywords       = {review, vSLAM, rank4, qualityAssured},
  owner          = {y},
  publisher      = {Taylor \& Francis},
  timestamp      = {2014.08.24},
}

@Article{Chen2012,
  author =    {Chen, S. Y.},
  title =     {Kalman Filter for Robot Vision: A Survey},
  journal =   {IEEE Transactions on Industrial Electronics},
  year =      {2012},
  volume =    {59},
  number =    {11},
  pages =     {4409--4420},
  file =      {Published version:Chen2012.pdf:PDF},
  keywords =  {EKF, survey, rank3},
  owner =     {GaoXiang},
  timestamp = {2014.01.13}
}

@InProceedings{Cheng2014,
  Title                    = {BING: Binarized normed gradients for objectness estimation at 300fps},
  Author                   = {Cheng, Ming-Ming and Zhang, Ziming and Lin, Wen-Yan and Torr, Philip},
  Booktitle                = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
  Year                     = {2014},
  Organization             = {IEEE},
  Pages                    = {3286--3293},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Choi2014,
  Title                    = {Simultaneous Global Localization and Mapping},
  Author                   = {Hyukdoo Choi and Kwang Woong Yang and Euntai Kim},
  Journal                  = {IEEE/ASME Transactions on Mechatronics},
  Year                     = {2014},

  Month                    = {\#aug\#},
  Number                   = {4},
  Pages                    = {1160--1170},
  Volume                   = {19},

  File                     = {Published version:Choi2014.pdf:PDF},
  ISSN                     = {1083-4435},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Choi2014a,
  Title                    = {Simultaneous Global Localization and Mapping},
  Author                   = {Hyukdoo Choi and Kwang Woong Yang and Euntai Kim},
  Journal                  = {Mechatronics, IEEE/ASME Transactions on},
  Year                     = {2014},

  Month                    = {Aug},
  Number                   = {4},
  Pages                    = {1160-1170},
  Volume                   = {19},

  Doi                      = {10.1109/TMECH.2013.2274822},
  ISSN                     = {1083-4435},
  Keywords                 = {SLAM (robots);mobile robots;robot vision;SLAM technique;SiGLAM technique;global localization feature-driven method;hypothesis scoring;sensor noise robustness;simultaneous global localization and mapping;Equations;Mathematical model;Noise;Simultaneous localization and mapping;Vectors;Global localization;imperfect map;partially known map;simultaneous localization and mapping (SLAM)},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Chow1968,
  author    = {Chow, C and Liu, C},
  title     = {Approximating discrete probability distributions with dependence trees},
  journal   = {IEEE transactions on Information Theory},
  year      = {1968},
  volume    = {14},
  number    = {3},
  pages     = {462--467},
  owner     = {cyang},
  publisher = {IEEE},
  timestamp = {2016.10.01},
}

@Article{Churchill2013,
  Title                    = {Experience-based navigation for long-term localisation},
  Author                   = {Churchill, Winston and Newman, Paul},
  Journal                  = {International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1645--1661},
  Volume                   = {32},

  Abstract                 = {This paper is about long-term navigation in environments whose appearance changes over time, suddenly or gradually. We describe, implement and validate an approach which allows us to incrementally learn a model whose complexity varies naturally in accordance with variation of scene appearance. It allows us to leverage the state of the art in pose estimation to build over many runs, a world model of sufficient richness to allow simple localisation despite a large variation in conditions. As our robot repeatedly traverses its workspace, it accumulates distinct visual experiences that in concert, implicitly represent the scene variation: each experience captures a visual mode. When operating in a previously visited area, we continually try to localise in these previous experiences while simultaneously running an independent vision-based pose estimation system. Failure to localise in a sufficient number of prior experiences indicates an insufficient model of the workspace and instigates the laying down of the live image sequence as a new distinct experience. In this way, over time we can capture the typical time-varying appearance of an environment and the number of experiences required tends to a constant. Although we focus on vision as a primary sensor throughout, the ideas we present here are equally applicable to other sensor modalities. We demonstrate our approach working on a road vehicle operating over a 3-month period at different times of day, in different weather and lighting conditions. We present extensive results analysing different aspects of the system and approach, in total processing over 136,000 frames captured from 37 km of driving.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1645},
  File                     = {Published version:Churchill2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Civera2008,
  author    = {Civera, Javier and Davison, Andrew J and Montiel, JM Martinez},
  title     = {Inverse depth parametrization for monocular SLAM},
  journal   = {IEEE transactions on robotics},
  year      = {2008},
  volume    = {24},
  number    = {5},
  pages     = {932--945},
  publisher = {IEEE},
}

@InProceedings{Civera2011,
  author         = {Civera, Javier and G{\'a}lvez-L{\'o}pez, Dorian and Riazuelo, Luis and Tard{\'o}s, Juan D and Montiel, JMM},
  title          = {Towards semantic SLAM using a monocular camera},
  booktitle      = {Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on},
  year           = {2011},
  pages          = {1277--1284},
  organization   = {IEEE},
  file           = {Civera2011.pdf:Civera2011.pdf:PDF},
  keywords       = {qualityAssured, rank3},
  owner          = {x},
  timestamp      = {2015.05.24},
}

@InProceedings{Clemente2007,
  Title                    = {Mapping Large Loops with a Single Hand-Held Camera.},
  Author                   = {Clemente, Laura A and Davison, Andrew J and Reid, Ian D and Neira, Jos{\'e} and Tard{\'o}s, Juan D},
  Booktitle                = {Robotics: Science and Systems},
  Year                     = {2007},
  Pages                    = {11},
  Volume                   = {2},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@InProceedings{Collet2011,
  Title                    = {Structure discovery in multi-modal data: a region-based approach},
  Author                   = {Collet, Alvaro and Srinivasa, Siddhartha S and Hebert, Martial},
  Booktitle                = {Robotics and Automation (ICRA), 2011 IEEE International Conference on},
  Year                     = {2011},
  Organization             = {IEEE},
  Pages                    = {5695--5702},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Correa2012,
  Title                    = {Mobile Robots Navigation in Indoor Environments Using Kinect Sensor},
  Author                   = {Correa, D. S. O. and Sciotti, D. F. and Prado, M. G. and Sales, D. O. and Wolf, D. F. and Osorio, F. S.},
  Journal                  = {2012 Second Brazilian Conference on Critical Embedded Systems (CBSEC 2012)},
  Year                     = {2012},
  Pages                    = {36--41},

  File                     = {Published version:Correa2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.04.19}
}

@Article{Couprie2013,
  Title                    = {Indoor semantic segmentation using depth information},
  Author                   = {Couprie, Camille and Farabet, Cl{\'e}ment and Najman, Laurent and LeCun, Yann},
  Journal                  = {arXiv preprint arXiv:1301.3572},
  Year                     = {2013},

  File                     = {Couprie2013.pdf:Couprie2013.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Cummins2008,
  Title                    = {FAB-MAP: Probabilistic localization and mapping in the space of appearance},
  Author                   = {Cummins, Mark and Newman, Paul},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2008},
  Number                   = {6},
  Pages                    = {647--665},
  Volume                   = {27},

  __markedentry            = {[y:5]},
  File                     = {:Cummins2008.pdf:PDF},
  Keywords                 = {FAB-MAP, important},
  Owner                    = {y},
  Publisher                = {SAGE Publications},
  Timestamp                = {2014.04.16},
  Url                      = {http://ijr.sagepub.com/content/27/6/647.full.pdf}
}

@Article{Cummins2010,
  Title                    = {Accelerating FAB-{MAP} With Concentration Inequalities},
  Author                   = {Cummins, Mark and Newman, Paul},
  Journal                  = {IEEE Transactions On Robotics},
  Year                     = {2010},
  Number                   = {6},
  Pages                    = {1042--1050},
  Volume                   = {26},

  File                     = {Published version:Cummins2010.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Cummins2011,
  author         = {Cummins, Mark and Newman, Paul},
  title          = {Appearance-only SLAM at large scale with FAB-MAP 2.0},
  journal        = {International Journal of Robotics Research},
  year           = {2011},
  volume         = {30},
  number         = {9},
  pages          = {1100--1123},
  comment        = {著名的FAB-MAP 2.0，做Loop closure的一定要和它去比，不然不完整�?????? 14.11.20 粗略过了�??????遍，FAB-MAP也是基于BoW模型�?????? 感觉LC都是用在很大的场合，本文用的数据高达1000km，全是室外场景，�??????40m之内就算是一个loop。这和Kinect的小而复杂的场景还是非常不一样的�?????? precision-recall曲线的计算： p = true positive / total loops; r = true positive / ground truth 训练方法：在路径上每隔一段取出一张图片，组成训练集�?�对模型训练完毕后，再测试其他的图像，验证是否出现闭环�?�},
  file           = {Published version:Cummins2011.pdf:PDF},
  keywords       = {loop closure, FAB-MAP, rank5, qualityAssured},
  owner          = {GaoXiang},
  timestamp      = {2014.01.13},
}

@Article{Dardari2015,
  Title                    = {Indoor Tracking: Theory, Methods, and Technologies},
  Author                   = {Dardari, D. and Closas, P. and Djuric, P.M.},
  Journal                  = {Vehicular Technology, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {April},
  Number                   = {4},
  Pages                    = {1263-1278},
  Volume                   = {64},

  Doi                      = {10.1109/TVT.2015.2403868},
  ISSN                     = {0018-9545},
  Keywords                 = {Global Positioning System;mobile communication;signal processing;GPS;global positioning system;high-definition real-time tracking systems;indoor environments;indoor localization;indoor scenarios;indoor tracking;indoor tracking problem;indoor wireless tracking;mobile nodes;outdoor tracking;satellite technologies;signal processing perspective;Accuracy;Estimation;Magnetometers;Mobile nodes;Position measurement;Wireless communication;Bayesian filtering;Indoor tracking;data fusion;indoor tracking;simultaneous localization;simultaneous localization and mapping (SLAM);technologies for tracking},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Davison2003,
  author       = {Davison, Andrew J},
  title        = {Real-time simultaneous localisation and mapping with a single camera},
  booktitle    = {Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on},
  year         = {2003},
  pages        = {1403--1410},
  organization = {IEEE},
}

@Article{Davison2007,
  author         = {Davison, AJ. and Reid, ID. and Molton, N.D. and Stasse, O.},
  title          = {MonoSLAM: Real-Time Single Camera {SLAM}},
  journal        = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year           = {2007},
  volume         = {29},
  number         = {6},
  pages          = {1052--1067},
  issn           = {0162-8828},
  __markedentry  = {[y:5]},
  comment        = {MonoSLAM�????????????经典之作，Davison大大的，英文也写的非常好。},
  file           = {Published version:Davison2007.pdf:PDF},
  keywords       = {mono slam, important, classic, rank5, qualityAssured},
  owner          = {y},
  timestamp      = {2014.08.24},
}

@Article{Dellaert2012,
  author    = {Dellaert, Frank},
  title     = {Factor graphs and GTSAM: A hands-on introduction},
  year      = {2012},
  publisher = {Georgia Institute of Technology},
}

@InProceedings{Deng2013,
  Title                    = {Recent advances in deep learning for speech research at Microsoft},
  Author                   = {Deng, Li and Li, Jinyu and Huang, Jui-Ting and Yao, Kaisheng and Yu, Dong and Seide, Frank and Seltzer, Michael and Zweig, Geoffrey and He, Xiaodong and Williams, Jason and others},
  Booktitle                = {Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {8604--8608},

  Owner                    = {zero},
  Timestamp                = {2015.04.09}
}

@InBook{DominguezQuijada2013,
  Title                    = {Fast 6D Odometry Based on Visual Features and Depth},
  Author                   = {Dominguez Quijada, Salvador and Zalama, Eduardo and Gomez Garcia-Bermejo, Jaime and Worst, Rainer and Behnke, Sven},
  Editor                   = {Lee, S. and Cho, H. S. and Yoon, K. J. and Lee, J. M.},
  Pages                    = {245--256},
  Year                     = {2013},
  Series                   = {Advances in Intelligent Systems and Computing},
  Type                     = {Book Section},
  Volume                   = {193},

  Booktitle                = {Intelligent Autonomous Systems 12, Vol 1},
  File                     = {DominguezQuijada2013.pdf:DominguezQuijada2013.pdf:PDF},
  ISBN                     = {2194-5357 978-3-642-33925-7},
  Owner                    = {x},
  Timestamp                = {2014.10.19}
}

@Article{Dou2016,
  author    = {Dou, Mingsong and Khamis, Sameh and Degtyarev, Yury and Davidson, Philip and Fanello, Sean Ryan and Kowdle, Adarsh and Escolano, Sergio Orts and Rhemann, Christoph and Kim, David and Taylor, Jonathan and others},
  title     = {Fusion4D: real-time performance capture of challenging scenes},
  journal   = {ACM Transactions on Graphics (TOG)},
  year      = {2016},
  volume    = {35},
  number    = {4},
  pages     = {114},
  publisher = {ACM},
}

@InProceedings{Drost2010,
  Title                    = {Model globally, match locally: Efficient and robust 3D object recognition},
  Author                   = {Drost, Bertram and Ulrich, Markus and Navab, Nassir and Ilic, Slobodan},
  Booktitle                = {2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  Year                     = {2010},
  Organization             = {IEEE},
  Pages                    = {998--1005},

  File                     = {Published version:Drost2010.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Dubbelman2015,
  Title                    = {COP-SLAM: Closed-Form Online Pose-Chain Optimization for Visual SLAM},
  Author                   = {Dubbelman, G. and Browning, B.},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {Oct},
  Number                   = {5},
  Pages                    = {1194-1213},
  Volume                   = {31},

  Doi                      = {10.1109/TRO.2015.2473455},
  File                     = {Dubbelman2015.pdf:Dubbelman2015.pdf:PDF},
  ISSN                     = {1552-3098},
  Keywords                 = {Accuracy;Image edge detection;Optimization;Simultaneous localization and mapping;Trajectory;Visualization;Computer vision;pose-graph optimization;simultaneous localization and mapping (SLAM)},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Eade2009,
  Title                    = {Edge landmarks in monocular SLAM},
  Author                   = {Eade, Ethan and Drummond, Tom},
  Journal                  = {Image and Vision Computing},
  Year                     = {2009},
  Number                   = {5},
  Pages                    = {588--596},
  Volume                   = {27},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.18}
}

@Article{Einhorn2014,
  author    = {Einhorn, Erik and Gross, Horst-Michael},
  title     = {Generic NDT mapping in dynamic environments and its application for lifelong SLAM},
  journal   = {Robotics and Autonomous Systems},
  year      = {2014},
  comment   = {动�?�环境下建NDT地图，可以检测出行人。使用Kinect+Laser},
  file      = {Einhorn2014.pdf:Einhorn2014.pdf:PDF},
  keywords  = {rank3},
  owner     = {x},
  publisher = {Elsevier},
  timestamp = {2015.05.19},
}

@Article{Ekvall2006,
  Title                    = {Integrating active mobile robot object recognition and SLAM in natural environments},
  Author                   = {Ekvall, Staffan and Jensfelt, Patric and Kragic, Danica},
  Journal                  = {2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vols 1-12},
  Year                     = {2006},
  Pages                    = {5792--5797},

  File                     = {Published version:Ekvall2006.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Ekvall2007,
  Title                    = {Object detection and mapping for service robot tasks},
  Author                   = {Ekvall, Staffan and Kragic, Danica and Jensfelt, Patric},
  Journal                  = {Robotica},
  Year                     = {2007},
  Number                   = {02},
  Pages                    = {175--187},
  Volume                   = {25},

  File                     = {Published version:Ekvall2007.pdf:PDF},
  Owner                    = {GaoXiang},
  Publisher                = {Cambridge Univ Press},
  Timestamp                = {2014.01.13}
}

@InProceedings{Endres2012,
  author         = {Endres, Felix and Hess, J{\"u}rgen and Engelhard, Nikolas and Sturm, J{\"u}rgen and Cremers, Daniel and Burgard, Wolfram},
  title          = {An evaluation of the RGB-D {SLAM} system},
  booktitle      = {2012 IEEE International Conference on Robotics and Automation (ICRA)},
  year           = {2012},
  pages          = {1691--1696},
  organization   = {IEEE},
  __markedentry  = {[y:4]},
  file           = {Published version:Endres2012.pdf:PDF},
  keywords       = {rgb-d slam, graph-based slam, qualityAssured, rank4},
  owner          = {GaoXiang},
  timestamp      = {2014.03.18},
}

@InProceedings{Engel2013,
  author    = {Engel, Jakob and Sturm, Jurgen and Cremers, Daniel},
  title     = {Semi-dense visual odometry for a monocular camera},
  booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
  year      = {2013},
  pages     = {1449--1456},
  file      = {Engel2013.pdf:Engel2013.pdf:PDF},
}

@InCollection{Engel2014,
  author    = {Engel, Jakob and Sch{\"o}ps, Thomas and Cremers, Daniel},
  title     = {LSD-SLAM: Large-scale direct monocular SLAM},
  booktitle = {Computer Vision--ECCV 2014},
  publisher = {Springer},
  year      = {2014},
  pages     = {834--849},
  file      = {Engel2014.pdf:Engel2014.pdf:PDF},
  owner     = {x},
  timestamp = {2015.09.23},
}

@Article{Engel2016,
  author  = {Engel, Jakob and Koltun, Vladlen and Cremers, Daniel},
  title   = {Direct sparse odometry},
  journal = {arXiv preprint arXiv:1607.02565},
  year    = {2016},
  file    = {Engel2016.pdf:Engel2016.pdf:PDF},
}

@Article{Farabet2013,
  author         = {Farabet, Cl{\'e}ment and Couprie, Camille and Najman, Laurent and LeCun, Yann},
  title          = {Learning hierarchical features for scene labeling},
  journal        = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  year           = {2013},
  volume         = {35},
  number         = {8},
  pages          = {1915--1929},
  comment        = {Farabet大大的深度网络作品。和机器人关系不大，不过是图像领域的漂亮工作能够在短时间内分割图片，确定每部分内容是什么 15.1.13 这篇文章的工作很有启发意义。如果能明确图像里面的内容，无论做回环检测还是registration都会更方便。 15.9 Farabet和courpie几个人一直在用cnn搞rgbd场景认知，用的nyuv2数据集。出了好些文章。},
  file           = {Farabet2013.pdf:Farabet2013.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {x},
  publisher      = {IEEE},
  timestamp      = {2014.10.28},
}
@article{faugeras1988motion,
title={Motion and structure from motion in a piecewise planar environment},
author={Faugeras, Olivier D and Lustman, Francis},
journal={International Journal of Pattern Recognition and Artificial Intelligence},
volume={2},
number={03},
pages={485--508},
year={1988},
publisher={World Scientific}
}
@inproceedings{faugeras1992camera,
  title={Camera self-calibration: Theory and experiments},
  author={Faugeras, Olivier D and Luong, Q-T and Maybank, Stephen J},
  booktitle={European conference on computer vision},
  pages={321--334},
  year={1992},
  organization={Springer}
}

@InProceedings{Filliat2007,
  Title                    = {A visual bag of words method for interactive qualitative localization and mapping},
  Author                   = {Filliat, David},
  Booktitle                = {2007 IEEE International Conference on Robotics and Automation (ICRA)},
  Year                     = {2007},
  Organization             = {IEEE},
  Pages                    = {3921--3926},

  Owner                    = {x},
  Timestamp                = {2015.01.03}
}

@Article{Fioraio2013,
  author         = {Fioraio, N. and Di Stefano, L.},
  title          = {Joint Detection, Tracking and Mapping by Semantic Bundle Adjustment},
  journal        = {2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year           = {2013},
  pages          = {1538--45},
  comment        = {把物体分割和提取结合到SLAM中，能够提高建图的精度。},
  file           = {Published version:Fioraio2013.pdf:PDF},
  keywords       = {qualityAssured, rank3},
  owner          = {GaoXiang},
  timestamp      = {2014.01.13},
}

@Article{Fischler1981,
  author    = {Fischler, Martin A and Bolles, Robert C},
  title     = {Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography},
  journal   = {Communications of the ACM},
  year      = {1981},
  volume    = {24},
  number    = {6},
  pages     = {381--395},
  comment   = {ransac},
  owner     = {x},
  publisher = {ACM},
  timestamp = {2014.12.09},
}

@InProceedings{Forster2014,
  author       = {Forster, Christian and Pizzoli, Matia and Scaramuzza, Davide},
  title        = {SVO: Fast semi-direct monocular visual odometry},
  booktitle    = {Robotics and Automation (ICRA), 2014 IEEE International Conference on},
  year         = {2014},
  editor       = {rs},
  pages        = {15--22},
  organization = {IEEE},
  file         = {:Foster2014.pdf:PDF},
  owner        = {x},
  timestamp    = {2015.09.23},
}

@Article{Fuentes-Pacheco2015,
  Title                    = {Visual simultaneous localization and mapping: a survey},
  Author                   = {Fuentes-Pacheco, Jorge and Ruiz-Ascencio, Jos{\'e} and Rend{\'o}n-Mancha, Juan Manuel},
  Journal                  = {Artificial Intelligence Review},
  Year                     = {2015},
  Number                   = {1},
  Pages                    = {55--81},
  Volume                   = {43},

  File                     = {Fuentes-Pacheco2015.pdf:Fuentes-Pacheco2015.pdf:PDF},
  Owner                    = {zero},
  Publisher                = {Springer},
  Timestamp                = {2015.05.17}
}

@Article{Galvez-Lopez2012,
  Title                    = {Bags of Binary Words for Fast Place Recognition in Image Sequences},
  Author                   = {Galvez-Lopez, Dorian and Tardos, Juan D.},
  Journal                  = {IEEE Transactions On Robotics},
  Year                     = {2012},
  Number                   = {5},
  Pages                    = {1188--1197},
  Volume                   = {28},

  File                     = {Published version:Galvez-Lopez2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Ganganath2012,
  Title                    = {Mobile robot localization using odometry and kinect sensor},
  Author                   = {Ganganath, N. and Leung, H.},
  Journal                  = {2012 IEEE International Conference on Emerging Signal Processing Applications},
  Year                     = {2012},
  Pages                    = {91--4},

  __markedentry            = {[y:1]},
  File                     = {Published version:Ganganath2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Gao2015,
  author       = {Gao, Xiang and Zhang, Tao},
  title        = {Loop closure detection for visual slam systems using deep neural networks},
  booktitle    = {Control Conference (CCC), 2015 34th Chinese},
  year         = {2015},
  pages        = {5851--5856},
  organization = {IEEE},
}

@Article{Gao2015a,
  Title                    = {Robust RGB-D simultaneous localization and mapping using planar point features},
  Author                   = {Gao, Xiang and Zhang, Tao},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2015},
  Pages                    = {1-14},
  Volume                   = {72},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.09.10}
}

@Article{GaoHouTangEtAl2003,
  author =   {Xiao-Shan Gao and Xiao-Rong Hou and Jianliang Tang and Hang-Fei Cheng},
  title =    {Complete solution classification for the perspective-three-point problem},
  journal =  {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year =     {2003},
  volume =   {25},
  number =   {8},
  pages =    {930-943},
  month =    {Aug},
  doi =      {10.1109/TPAMI.2003.1217599},
  issn =     {0162-8828},
  keywords = {computational geometry;computer vision;polynomials;CASSC;P3P equation system;algebraic approach;complete solution classification;geometric approach;perspective-three-point problem;pose estimation;triangular decomposition;zero decomposition algorithm;Algorithm design and analysis;Automatic control;Calibration;Cameras;Equations;Helium;Layout;Robot vision systems;Robotics and automation;Robustness}
}

@Article{Garcia-Fidalgo2015,
  Title                    = {Vision-based topological mapping and localization methods: A survey},
  Author                   = {Garcia-Fidalgo, Emilio and Ortiz, Alberto},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2015},
  Pages                    = {1--20},
  Volume                   = {64},

  File                     = {Garcia-Fidalgo2015.pdf:Garcia-Fidalgo2015.pdf:PDF},
  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.09.09}
}

@Article{Gauglitz2014,
  Title                    = {Model Estimation and Selection towards Unconstrained Real-Time Tracking and Mapping},
  Author                   = {Gauglitz, S. and Sweeney, C. and Ventura, J. and Turk, M. and Hollerer, T.},
  Journal                  = {IEEE Transactions on Visualization and Computer Graphics},
  Year                     = {2014},
  Number                   = {6},
  Pages                    = {825--838},
  Volume                   = {20},

  ISSN                     = {1077-2626},
  Keywords                 = {Visual tracking simultaneous localization and mapping panorama mapping model selection GRIC score keyframe-based initialization-free augmented reality monocular slam},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Gavshinde2013,
  Title                    = {Trajectory planning for monocular {SLAM} systems},
  Author                   = {Gavshinde, L. and Singh, A. K. and Krishna, K. M.},
  Journal                  = {2013 IEEE International Conference on Control Applications (CCA). Part of 2013 IEEE Multi-Conference on Systems and Control},
  Year                     = {2013},
  Pages                    = {631--6},

  File                     = {Published version:Gavshinde2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Gee2008,
  Title                    = {Discovering Higher Level Structure in Visual SLAM},
  Author                   = {Gee, AP. and Chekhlov, D. and Calway, A and Mayol-Cuevas, W.},
  Journal                  = {IEEE Transactions on Robotics},
  Year                     = {2008},
  Number                   = {5},
  Pages                    = {980--990},
  Volume                   = {24},

  File                     = {Published version:Gee2008.pdf:PDF},
  ISSN                     = {1552-3098},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Geiger2012,
  Title                    = {Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite},
  Author                   = {Geiger, Andreas and Lenz, Philip and Urtasun, Raquel},
  Journal                  = {2012 IEEE Conference On Computer Vision And Pattern Recognition (cvpr)},
  Year                     = {2012},
  Pages                    = {3354--3361},

  File                     = {Published version:Geiger2012.pdf:PDF},
  Keywords                 = {benchmark},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Geiger2013,
  Title                    = {Vision meets Robotics: The KITTI Dataset},
  Author                   = {Geiger, A and Lenz, P and Stiller, C and Urtasun, R},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},

  Abstract                 = {We present a novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research. In total, we recorded 6 hours of traffic scenarios at 10--Hz using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras, a Velodyne 3D laser scanner and a high-precision GPS/IMU inertial navigation system. The scenarios are diverse, capturing real-world traffic situations, and range from freeways over rural areas to inner-city scenes with many static and dynamic objects. Our data is calibrated, synchronized and timestamped, and we provide the rectified and raw image sequences. Our dataset also contains object labels in the form of 3D tracklets, and we provide online benchmarks for stereo, optical flow, object detection and other tasks. This paper describes our recording platform, the data format and the utilities that we provide.},
  Eprint                   = {http://ijr.sagepub.com/content/early/2013/08/22/0278364913491297.full.pdf+html},
  File                     = {Published version:Geiger2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Gil2010,
  Title                    = {A comparative evaluation of interest point detectors and local descriptors for visual SLAM},
  Author                   = {Gil, Arturo and Mozos, Oscar Martinez and Ballesta, Monica and Reinoso, Oscar},
  Journal                  = {Machine Vision and Applications},
  Year                     = {2010},
  Number                   = {6},
  Pages                    = {905--920},
  Volume                   = {21},

  __markedentry            = {[y:4]},
  File                     = {Gil2010.pdf:Gil2010.pdf:PDF},
  Owner                    = {y},
  Publisher                = {Springer},
  Timestamp                = {2014.09.04}
}

@Article{Gil2010a,
  author         = {Gil, A. and Reinoso, O. and Ballesta, M. and Julia, M.},
  title          = {Multi-robot visual SLAM using a Rao-Blackwellized particle filter},
  journal        = {Robotics and Autonomous Systems},
  year           = {2010},
  volume         = {58},
  number         = {1},
  pages          = {68--80},
  issn           = {0921-8890},
  comment        = {14.10.27 只看了摘要�?? 讲multi robot SLAM的文章�?�经典的特征思路。小型机器人群�?�},
  file           = {Gil2010.pdf:Gil2010a.pdf:PDF},
  keywords       = {SLAM Cooperative robots Particle filter Visual landmarks mobile robot localization, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Glocker2015,
  Title                    = {Real-Time RGB-D Camera Relocalization via Randomized Ferns for Keyframe Encoding},
  Author                   = {Glocker, B. and Shotton, J. and Criminisi, A. and Izadi, S.},
  Journal                  = {Visualization and Computer Graphics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {May},
  Number                   = {5},
  Pages                    = {571-583},
  Volume                   = {21},

  Doi                      = {10.1109/TVCG.2014.2360403},
  ISSN                     = {1077-2626},
  Keywords                 = {SLAM (robots);cameras;image coding;image colour analysis;image representation;image retrieval;object tracking;pose estimation;BlockHD;automatic keyframe discovery;binary feature tests;block code concatenation;block-wise hamming distance;code tables;frame dissimilarity;frame-pose pair;global compact camera frame representation;hand-held KinectFusion system;image co-occurrences;incoming query frame;keyframe encoding;keyframe-based relocalization method;node traversal;online harvesting;pose retrieval;randomized ferns;real-time RGB-D camera relocalization;simultaneous localization and tracking system;tracking algorithm reinitialization;tracking failure recovery;tracking mode;Cameras;Encoding;Image reconstruction;Pipelines;Real-time systems;Simultaneous localization and mapping;Three-dimensional displays;Camera relocalization;camera relocalization;dense tracking and mapping;marker-free augmented reality;tracking recovery},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Gouveia2015,
  Title                    = {Computation Sharing in Distributed Robotic Systems: A Case Study on SLAM},
  Author                   = {Gouveia, B.D. and Portugal, D. and Silva, D.C. and Marques, L.},
  Journal                  = {Automation Science and Engineering, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {April},
  Number                   = {2},
  Pages                    = {410-422},
  Volume                   = {12},

  Doi                      = {10.1109/TASE.2014.2357216},
  ISSN                     = {1545-5955},
  Keywords                 = {SLAM (robots);mobile robots;multi-robot systems;SLAM;computation sharing;distributed robotic systems;localization precision;map accuracy;mobile robots;network bandwidth;simultaneous localization and mapping;Computer architecture;Context;Multi-robot systems;Robot kinematics;Simultaneous localization and mapping;Distributed computing;networked robots;robotic clusters;simultaneous localization and mapping;task sharing in multirobot systems},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Granstrom2011,
  Title                    = {Learning to close loops from range data},
  Author                   = {Granstrom, Karl and Schon, Thomas B. and Nieto, Juan I. and Ramos, Fabio T.},
  Journal                  = {International Journal Of Robotics Research},
  Year                     = {2011},
  Number                   = {14},
  Pages                    = {1728--1754},
  Volume                   = {30},

  File                     = {Published version:Granstrom2011.pdf:PDF},
  Keywords                 = {loop closure},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Granstrom2014,
  Title                    = {Random Set Methods: Estimation of Multiple Extended Objects},
  Author                   = {Granstrom, K. and Lundquist, C. and Gustafsson, F. and Orguner, U.},
  Journal                  = {Robotics Automation Magazine, IEEE},
  Year                     = {2014},

  Month                    = {June},
  Number                   = {2},
  Pages                    = {73-82},
  Volume                   = {21},

  Doi                      = {10.1109/MRA.2013.2283185},
  ISSN                     = {1070-9932},
  Keywords                 = {Bayes methods;SLAM (robots);mobile robots;object tracking;random processes;state estimation;Bayesian framework;Bayesian state estimation;RFS estimation;SLAM;autonomous robot vehicle;extended object estimation;extended-object tracking;laser range data;multiple extended object estimation;point object estimation;random finite set estimation;sensor;Bayes methods;Estimation;Object tracking;Robot sensing systems;Surveillance;Time measurement},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Grasa2011,
  Title                    = {EKF monocular SLAM with relocalization for laparoscopic sequences},
  Author                   = {Grasa, Oscar G and Civera, Javier and Montiel, JMM},
  Booktitle                = {Robotics and Automation (ICRA), 2011 IEEE International Conference on},
  Year                     = {2011},
  Organization             = {IEEE},
  Pages                    = {4816--4821},

  Owner                    = {x},
  Timestamp                = {2015.05.17}
}

@Article{Grigorescu2011,
  Title                    = {Robust camera pose and scene structure analysis for service robotics},
  Author                   = {Grigorescu, Sorin M. and Macesanu, Gigel and Cocias, Tiberiu T. and Puiu, Dan and Moldoveanu, Florin},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2011},
  Number                   = {11},
  Pages                    = {899--909},
  Volume                   = {59},

  File                     = {Published version:Grigorescu2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Grisetti2007,
  author       = {Grisetti, Giorgio and Grzonka, Slawomir and Stachniss, Cyrill and Pfaff, Patrick and Burgard, Wolfram},
  title        = {Efficient estimation of accurate maximum likelihood maps in 3d},
  booktitle    = {Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on},
  year         = {2007},
  pages        = {3472--3478},
  organization = {IEEE},
  comment      = {TORO的引用},
  owner        = {x},
  timestamp    = {2014.12.09},
}

@Article{Grisetti2010,
  Title                    = {A Tutorial on Graph-Based SLAM},
  Author                   = {Grisetti, G. and Kümmerle, R. and Stachniss, C. and Burgard, W.},
  Journal                  = {Intelligent Transportation Systems Magazine, IEEE},
  Year                     = {2010},

  Month                    = {winter},
  Number                   = {4},
  Pages                    = {31-43},
  Volume                   = {2},

  Doi                      = {10.1109/MITS.2010.939925},
  ISSN                     = {1939-1390},
  Keywords                 = {SLAM (robots);mobile robots;path planning;graph based SLAM;least square error minimization;mobile robot;navigation;simultaneous localization and mapping;spatial configuration;Global Positioning System;Graph theory;Mapping;Mobile robots;Tutorials},
  Owner                    = {x},
  Timestamp                = {2015.10.21}
}

@InCollection{Guenther2011,
  Title                    = {Model-Based Object Recognition from 3D Laser Data},
  Author                   = {Guenther, Martin and Wiemann, Thomas and Albrecht, Sven and Hertzberg, Joachim},
  Year                     = {2011},
  Pages                    = {99--110},
  Volume                   = {7006},

  Doi                      = {10.1007/978-3-642-24455-1_9},
  File                     = {Published version:Guenther2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Guerra2014,
  author =        {Guerra, Edmundo and Munguia, Rodrigo and Grau, Antoni},
  title =         {Monocular SLAM for Autonomous Robots with Enhanced Features Initialization},
  journal =       {Sensors},
  year =          {2014},
  volume =        {14},
  number =        {4},
  pages =         {6317--6337},
  __markedentry = {[y:3]},
  file =          {Published version:Guerra2014.pdf:PDF},
  keywords =      {monocular SLAM, rank1},
  owner =         {y},
  publisher =     {Multidisciplinary Digital Publishing Institute},
  timestamp =     {2014.08.25}
}

@PhdThesis{Guivant2002,
  Title                    = {Efficient simultaneous localization and mapping in large environments},
  Author                   = {Guivant, Jose E},
  School                   = {Citeseer},
  Year                     = {2002},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@InProceedings{Gupta2013,
  Title                    = {Perceptual organization and recognition of indoor scenes from RGB-D images},
  Author                   = {Gupta, Saurabh and Arbelaez, Pablo and Malik, Jitendra},
  Booktitle                = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {564--571},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Gupta2014,
  author         = {Gupta, Saurabh and Arbel{\'a}ez, Pablo and Girshick, Ross and Malik, Jitendra},
  title          = {Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation},
  journal        = {International Journal of Computer Vision},
  year           = {2014},
  pages          = {1--17},
  __markedentry  = {[x:]},
  comment        = {RGB-D图像的分割、物体识别与检测。很全的文章。 然而这像是个纯视觉问题，在单张图像上面做文章，和SLAM关系不大的样子。},
  file           = {Gupta2014.pdf:Gupta2014.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {x},
  publisher      = {Springer},
  timestamp      = {2015.05.26},
}

@InCollection{Gupta2014a,
  author =         {Saurabh Gupta and Ross Girshick and Pablo Arbelaez and Jitendra Malik},
  title =          {Learning Rich Features from {RGB-D} Images for Object Detection and Segmentation},
  booktitle =      {ECCV},
  year =           {2014},
  file =           {Gupta2014a.pdf:Gupta2014a.pdf:PDF},
  keywords =       {qualityAssured, rank4},
  owner =          {x},
  timestamp =      {2015.11.17}
}

@InProceedings{Hahnel2003,
  author       = {Hahnel, Dirk and Burgard, Wolfram and Fox, Dieter and Thrun, Sebastianrt},
  title        = {An efficient FastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements},
  booktitle    = {Intelligent Robots and Systems, 2003.(IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on},
  year         = {2003},
  volume       = {1},
  pages        = {206--211},
  organization = {IEEE},
  owner        = {zero},
  timestamp    = {2015.04.09},
}

@InProceedings{Handa2012,
  author       = {Handa, Ankur and Newcombe, Richard A and Angeli, Adrien and Davison, Andrew J},
  title        = {Real-time camera tracking: When is high frame-rate best?},
  booktitle    = {European Conference on Computer Vision},
  year         = {2012},
  pages        = {222--235},
  organization = {Springer},
}

@InProceedings{Hane2013,
  Title                    = {Joint 3D scene reconstruction and class segmentation},
  Author                   = {Hane, Christian and Zach, Christopher and Cohen, Andrea and Angst, Roland and Pollefeys, Marc},
  Booktitle                = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {97--104},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Hartley1997,
  author    = {Hartley, Richard I},
  title     = {In defense of the eight-point algorithm},
  journal   = {IEEE Transactions on pattern analysis and machine intelligence},
  year      = {1997},
  volume    = {19},
  number    = {6},
  pages     = {580--593},
  publisher = {IEEE},
}

@Book{Hartley2003,
  Title                    = {Multiple View Geometry in Computer Vision},
  Author                   = {Hartley, Richard and Zisserman, Andrew},
  Publisher                = {Cambridge university press},
  Year                     = {2003},

  Owner                    = {x},
  Timestamp                = {2014.12.10}
}

@InProceedings{Henry2010,
  author    = {Peter Henry and Michael Krainin and Evan Herbst and Xiaofeng Ren and Dieter Fox},
  title     = {RGB-D Mapping: Using depth cameras for dense 3D modeling of indoor environments},
  booktitle = {In the 12th International Symposium on Experimental Robotics ISER},
  year      = {2010},
  comment   = {Henry大大14年IJRR作品的早期阶段�?�},
  owner     = {x},
  timestamp = {2014.10.11},
}

@Article{Henry2012,
  author         = {Henry, Peter and Krainin, Michael and Herbst, Evan and Ren, Xiaofeng and Fox, Dieter},
  title          = {RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments},
  journal        = {The International Journal of Robotics Research},
  year           = {2012},
  volume         = {31},
  number         = {5},
  pages          = {647--663},
  comment        = {和Endres大大并称的RGB-D SLAM大作�???????????? 虽然具体做的事情差不多�?�不过人家Endres大大是开源的。},
  file           = {Published version:Henry2012.pdf:PDF},
  keywords       = {rgb-d slam, important, graph-based slam, qualityAssured, rank5},
  owner          = {GaoXiang},
  publisher      = {SAGE Publications},
  timestamp      = {2014.03.17},
}

@Article{Herath2012,
  Title                    = {A two-tier map representation for compact-stereo-vision-based SLAM},
  Author                   = {Herath, D. C. and Kodagoda, S. and Dissanayake, G.},
  Journal                  = {Robotica},
  Year                     = {2012},
  Pages                    = {245--256},
  Volume                   = {30},

  ISSN                     = {0263-5747},
  Keywords                 = {SLAM Computer vision Navigation Robot localization Pose estimation and registration simultaneous localization human navigation filter environments eye},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Hesch2014,
  Title                    = {Consistency Analysis and Improvement of Vision-aided Inertial Navigation},
  Author                   = {Hesch, J.A and Kottas, D.G. and Bowman, S.L. and Roumeliotis, S.I},
  Journal                  = {IEEE Transactions on Robotics},
  Year                     = {2014},

  Month                    = {\#feb\#},
  Number                   = {1},
  Pages                    = {158--176},
  Volume                   = {30},

  File                     = {Published version:Hesch2014.pdf:PDF},
  ISSN                     = {1552-3098},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@InProceedings{Hirschmuller2007,
  author       = {Hirschmuller, Heiko and Scharstein, Daniel},
  title        = {Evaluation of cost functions for stereo matching},
  booktitle    = {2007 IEEE Conference on Computer Vision and Pattern Recognition},
  year         = {2007},
  pages        = {1--8},
  organization = {IEEE},
}

@Article{Ho2007,
  Title                    = {Detecting Loop Closure with Scene Sequences},
  Author                   = {Ho, KinLeong and Newman, Paul},
  Journal                  = {International Journal of Computer Vision},
  Year                     = {2007},
  Number                   = {3},
  Pages                    = {261--286},
  Volume                   = {74},

  File                     = {Published version:Ho2007.pdf:PDF},
  ISSN                     = {0920-5691},
  Language                 = {English},
  Owner                    = {y},
  Publisher                = {Kluwer Academic Publishers-Plenum Publishers},
  Timestamp                = {2014.08.24}
}

@Article{Holmes2013,
  Title                    = {Monocular SLAM with Conditionally Independent Split Mapping},
  Author                   = {Holmes, S. A. and Murray, D. W.},
  Journal                  = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  Year                     = {2013},
  Number                   = {6},
  Pages                    = {1451--1463},
  Volume                   = {35},

  ISSN                     = {0162-8828},
  Keywords                 = {Monocular SLAM relative bundle adjustment parallel tracking and mapping split-mapping submapping simultaneous localization real-time consistency algorithm monoslam camera},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Hornung2013,
  author =    {Hornung, Armin and Wurm, Kai M and Bennewitz, Maren and Stachniss, Cyrill and Burgard, Wolfram},
  title =     {OctoMap: An efficient probabilistic 3D mapping framework based on octrees},
  journal =   {Autonomous Robots},
  year =      {2013},
  volume =    {34},
  number =    {3},
  pages =     {189--206},
  file =      {Hornung2013.pdf:Hornung2013.pdf:PDF},
  keywords =  {rank4},
  owner =     {x},
  publisher = {Springer},
  timestamp = {2015.11.27}
}

@Article{Hou2015,
  Title                    = {Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection},
  Author                   = {Hou, Yi and Zhang, Hong and Zhou, Shilin},
  Journal                  = {arXiv preprint arXiv:1504.05241},
  Year                     = {2015},

  Owner                    = {x},
  Timestamp                = {2015.12.14}
}

@Article{Hygounenc2004,
  Title                    = {The Autonomous Blimp Project of LAAS-CNRS: Achievements in Flight Control and Terrain Mapping},
  Author                   = {Hygounenc, Emmanuel and Jung, Il-Kyun and Sou{\`{e}}res, Philippe and Lacroix, Simon},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2004},
  Number                   = {4-5},
  Pages                    = {473--511},
  Volume                   = {23},

  Abstract                 = {In this paper we provide a progress report of the LAAS-CNRS project of autonomous blimp robot development, in the context of field robotics. Hardware developments aimed at designing a generic and versatile experimental platform are first presented. On this base, the flight control and terrain mapping issues, which constitute the main thrust of the research work, are presented in two parts. The first part, devoted to the automatic control study, is based on a rigorous modeling of the airship dynamics. Considering the decoupling of the lateral and longitudinal dynamics, several flight phases are identified for which appropriate control strategies are proposed. The description focuses on the lateral steady navigation. In the second part of the paper, we present work on terrain mapping with lowaltitude stereovision. A simultaneous localization and map building approach based on an extended Kalman filter is depicted, with details on the identification of the various errors involved in the process. Experimental results show that positioning in the three-dimensional space with a centimeter accuracy can be achieved, thus allowing the possibility to build high-resolution digital elevation maps.},
  Eprint                   = {http://ijr.sagepub.com/content/23/4-5/473.full.pdf+html},
  Owner                    = {x},
  Timestamp                = {2014.10.05}
}

@Article{Innmann2016,
  author  = {Innmann, Matthias and Zollh{\"o}fer, Michael and Nie{\ss}ner, Matthias and Theobalt, Christian and Stamminger, Marc},
  title   = {VolumeDeform: Real-time Volumetric Non-rigid Reconstruction},
  journal = {arXiv preprint arXiv:1603.08161},
  year    = {2016},
}

@Article{Jin2013,
  Title                    = {Place recognition using straight lines for vision-based {SLAM}},
  Author                   = {Jin, Han Lee and Guoxuan, Zhang and Jongwoo, Lim and Il, Hong Suh},
  Journal                  = {2013 IEEE International Conference on Robotics and Automation (ICRA)},
  Year                     = {2013},
  Pages                    = {3799--806},

  File                     = {Published version:Jin2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Jin-fu2011,
  Title                    = {Research on object recognition using bag of word model for mobile robot navigation},
  Author                   = {Jin-fu, Yang and Kai, Wang and Ming-ai, Li and Lu, Liu},
  Journal                  = {Proceedings of the 2011 IEEE International Conference on Mechatronics and Automation (ICMA 2011)},
  Year                     = {2011},
  Pages                    = {1735--40},

  File                     = {Published version:Jin-fu2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Johnson-Roberson2010,
  author    = {Johnson-Roberson, Matthew and Pizarro, Oscar and Williams, Stefan B and Mahon, Ian},
  title     = {Generation and visualization of large-scale three-dimensional reconstructions from underwater robotic surveys},
  journal   = {Journal of Field Robotics},
  year      = {2010},
  volume    = {27},
  number    = {1},
  pages     = {21--51},
  comment   = {SLAM在水下机器人的应用},
  owner     = {x},
  publisher = {Wiley Online Library},
  timestamp = {2015.05.17},
}

@Article{Jones2011,
  author    = {Jones, E. S. and Soatto, S.},
  title     = {Visual-inertial navigation, mapping and localization: A scalable real-time causal approach},
  journal   = {International Journal of Robotics Research},
  year      = {2011},
  volume    = {30},
  number    = {4},
  pages     = {407--430},
  issn      = {0278-3649},
  comment   = {待读},
  file      = {Jones2011.pdf:Jones2011.pdf:PDF},
  keywords  = {Visual-inertial navigation simultaneous localization and mapping (SLAM) structure from motion vision-aided navigation vision-based navigation localization location recognition loop closure autonomous robotics assisted driving vehicle applications global localization motion features recognition calibration},
  owner     = {x},
  timestamp = {2014.10.19},
  type      = {Journal Article},
}

@Article{Julia2012,
  Title                    = {A comparison of path planning strategies for autonomous exploration and mapping of unknown environments},
  Author                   = {Julia, M. and Gil, A. and Reinoso, O.},
  Journal                  = {Autonomous Robots},
  Year                     = {2012},
  Number                   = {4},
  Pages                    = {427--444},
  Volume                   = {33},

  File                     = {Julia2012.pdf:Julia2012.pdf:PDF},
  ISSN                     = {0929-5593},
  Keywords                 = {Autonomous exploration Mapping of unknown environments Path planning for multiple mobile robot systems mobile robot navigation multirobot exploration simultaneous localization indoor environments slam algorithm vision},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Kaess2008,
  author    = {Kaess, Michael and Ranganathan, Ananth and Dellaert, Frank},
  title     = {iSAM: Incremental smoothing and mapping},
  journal   = {IEEE Transactions on Robotics},
  year      = {2008},
  volume    = {24},
  number    = {6},
  pages     = {1365--1378},
  publisher = {IEEE},
}

@Article{Kaess2010,
  Title                    = {Probabilistic structure matching for visual SLAM with a multi-camera rig},
  Author                   = {Kaess, Michael and Dellaert, Frank},
  Journal                  = {Computer Vision and Image Understanding},
  Year                     = {2010},
  Number                   = {2},
  Pages                    = {286--296},
  Volume                   = {114},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.18}
}

@Article{Kaess2011,
  author    = {Kaess, Michael and Johannsson, Hordur and Roberts, Richard and Ila, Viorela and Leonard, John J and Dellaert, Frank},
  title     = {iSAM2: Incremental smoothing and mapping using the Bayes tree},
  journal   = {The International Journal of Robotics Research},
  year      = {2011},
  pages     = {0278364911430419},
  publisher = {Sage Publications},
}

@Article{Kawewong2013,
  Title                    = {A speeded-up online incremental vision-based loop-closure detection for long-term {SLAM}},
  Author                   = {Kawewong, Aram and Tongprasit, Noppharit and Hasegawa, Osamu},
  Journal                  = {Advanced Robotics},
  Year                     = {2013},
  Number                   = {17},
  Pages                    = {1325--1336},
  Volume                   = {27},

  File                     = {Published version:Kawewong2013.pdf:PDF},
  Owner                    = {y},
  Publisher                = {Taylor \& Francis},
  Timestamp                = {2014.08.25}
}

@InProceedings{Kazhdan2006,
  author    = {Kazhdan, Michael and Bolitho, Matthew and Hoppe, Hugues},
  title     = {Poisson surface reconstruction},
  booktitle = {Proceedings of the fourth Eurographics symposium on Geometry processing},
  year      = {2006},
  volume    = {7},
}

@Article{Keidar2014,
  author         = {Keidar, M. and Kaminka, G. A.},
  title          = {Efficient frontier detection for robot exploration},
  journal        = {International Journal of Robotics Research},
  year           = {2014},
  volume         = {33},
  number         = {2},
  pages          = {215--236},
  issn           = {0278-3649},
  comment        = {关于探索（exploration）的文章，和SLAM没有直接的相关},
  file           = {Keidar2014.pdf:Keidar2014.pdf:PDF},
  keywords       = {sensor exploration Robotics SLAM frontier laser range multirobot exploration localization search, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Kerl2013,
  author       = {Kerl, Christian and Sturm, J{\"u}rgen and Cremers, Daniel},
  title        = {Robust odometry estimation for RGB-D cameras},
  booktitle    = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
  year         = {2013},
  pages        = {3748--3754},
  organization = {IEEE},
}

@InProceedings{Kerl2013a,
  author       = {Kerl, Christian and Sturm, J{\"u}rgen and Cremers, Daniel},
  title        = {Dense visual SLAM for RGB-D cameras},
  booktitle    = {2013 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year         = {2013},
  pages        = {2100--2106},
  organization = {IEEE},
}

@InProceedings{Khosoussi2015,
  Title                    = {Exploiting the Separable Structure of SLAM},
  Author                   = {Kasra Khosoussi AND Shoudong Huang AND Gamini Dissanayake},
  Booktitle                = {Proceedings of Robotics: Science and Systems},
  Year                     = {2015},

  Address                  = {Rome, Italy},
  Month                    = {July},

  File                     = {Khosoussi2015.pdf:Khosoussi2015.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2015.08.30}
}

@Article{Khosoussi2015a,
  author =    {Khosoussi, Kasra and Huang, Shoudong and Dissanayake, Gamini},
  title =     {Good, Bad and Ugly Graphs for SLAM},
  year =      {2015},
  file =      {Khosoussi2015a.pdf:Khosoussi2015a.pdf:PDF},
  keywords =  {rank3},
  owner =     {x},
  timestamp = {2015.08.30}
}

@Article{Kim2004,
  Title                    = {Autonomous airborne navigation in unknown terrain environments},
  Author                   = {Kim, Jonghyuk and Sukkarieh, Salah},
  Journal                  = {IEEE Transactions on Aerospace and Electronic Systems},
  Year                     = {2004},
  Number                   = {3},
  Pages                    = {1031--1045},
  Volume                   = {40},

  Keywords                 = {application,},
  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2014.10.05}
}

@Article{Kim2013,
  Title                    = {Occupancy Mapping and Surface Reconstruction Using Local {Gauss}ian Processes With Kinect Sensors},
  Author                   = {Kim, S. and Kim, J.},
  Journal                  = {IEEE Transactions on Cybernetics},
  Year                     = {2013},
  Number                   = {5},
  Pages                    = {1335--1346},
  Volume                   = {43},

  ISSN                     = {2168-2267},
  Keywords                 = {Continuous occupancy maps Gaussian processes RGB-D mapping surface reconstruction algorithm features maps},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Misc{Kitani2015,
  author    = {Kris Kitani},
  title     = {Lecture notes in Computer Vision},
  month     = {March},
  year      = {2015},
  publisher = {CMU 16-385 Computer Vision},
}

@Article{Klancar2014,
  Title                    = {Mobile-robot pose estimation and environment mapping using an extended {Kalman} filter},
  Author                   = {Klancar, G. and Teslic, L. and Skrjanc, I.},
  Journal                  = {International Journal of Systems Science},
  Year                     = {2014},
  Number                   = {12},
  Pages                    = {2603--2618},
  Volume                   = {45},

  ISSN                     = {0020-7721},
  Keywords                 = {wheeled mobile robot localisation mapping extended Kalman filter simultaneous localization line extraction range data algorithms slam representation laser},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@InProceedings{Klein2007,
  author       = {Klein, Georg and Murray, David},
  title        = {Parallel tracking and mapping for small AR workspaces},
  booktitle    = {Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on},
  year         = {2007},
  pages        = {225--234},
  organization = {IEEE},
  file         = {Klein2007.pdf:Klein2007.pdf:PDF},
  owner        = {x},
  timestamp    = {2015.05.17},
}

@InCollection{Klein2008,
  Title                    = {Improving the Agility of Keyframe-Based SLAM},
  Author                   = {Klein, Georg and Murray, David},
  Year                     = {2008},
  Pages                    = {802--815},
  Volume                   = {5303},

  File                     = {Published version:Klein2008.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Book{Koller2009,
  title     = {Probabilistic graphical models: principles and techniques},
  publisher = {MIT press},
  year      = {2009},
  author    = {Koller, Daphne and Friedman, Nir},
}

@InProceedings{Konda2015,
  Title                    = {Learning visual odometry with a convolutional network},
  Author                   = {Konda, Kishore and Memisevic, Roland},
  Booktitle                = {International Conference on Computer Vision Theory and Applications},
  Year                     = {2015},

  Owner                    = {x},
  Timestamp                = {2015.12.14}
}

@Article{Konolige2008,
  author         = {Konolige, K. and Agrawal, M.F},
  title          = {FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping},
  journal        = {IEEE Transactions on Robotics},
  year           = {2008},
  volume         = {24},
  number         = {5},
  pages          = {1066--1077},
  issn           = {1552-3098},
  __markedentry  = {[y:5]},
  comment        = {FrameSLAM：又�????????????经典大作�???????????? 把BA的�?�想融合进SLAM中，保留位姿约束，�?�放弃特征约束，从�?�大幅降低计算量。},
  file           = {Published version:Konolige2008.pdf:PDF},
  keywords       = {graph-based slam, frameslam, important, qualityAssured, rank5},
  owner          = {y},
  timestamp      = {2014.08.24},
}

@Article{Konolige2010,
  Title                    = {View-based Maps},
  Author                   = {Konolige, Kurt and Bowman, James and Chen, J. D. and Mihelich, Patrick and Calonder, Michael and Lepetit, Vincent and Fua, Pascal},
  Journal                  = {International Journal of Robotics Research},
  Year                     = {2010},
  Number                   = {8},
  Pages                    = {941--957},
  Volume                   = {29},

  File                     = {Published version:Konolige2010.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Koppula2011,
  author         = {Koppula, Hema S and Anand, Abhishek and Joachims, Thorsten and Saxena, Ashutosh},
  title          = {Semantic labeling of 3d point clouds for indoor scenes},
  booktitle      = {Advances in Neural Information Processing Systems},
  year           = {2011},
  pages          = {244--252},
  __markedentry  = {[x:]},
  comment        = {和我做的东西是很像，源代码能搞到，然而是ros D版的，比较久远。在H版上很难编译。},
  file           = {Koppula2011.pdf:Koppula2011.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {x},
  timestamp      = {2015.05.22},
}

@Article{Kostavelis2013,
  author         = {Kostavelis, I. and Gasteratos, A.},
  title          = {Learning spatially semantic representations for cognitive robot navigation},
  journal        = {Robotics and Autonomous Systems},
  year           = {2013},
  volume         = {61},
  number         = {12},
  pages          = {1460--1475},
  file           = {Kostavelis2013.pdf:Kostavelis2013.pdf:PDF},
  issn           = {0921-8890},
  keywords       = {Semantic mapping Spatial visual memories Place classification SLAM Neural Gas Bag-of-features Topological graph robust place recognition image features classification vision slam, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Kummerle2011,
  author         = {Kummerle, Rainer and Grisetti, Giorgio and Strasdat, Hauke and Konolige, Kurt and Burgard, Wolfram},
  title          = {G2o: a general framework for graph optimization},
  booktitle      = {IEEE International Conference on Robotics and Automation (ICRA)},
  year           = {2011},
  pages          = {3607--3613},
  organization   = {IEEE},
  __markedentry  = {[y:4]},
  comment        = {G2o库代码，用它的代码就要引用此文献。},
  file           = {Kummerle2011.pdf:Kummerle2011.pdf:PDF},
  keywords       = {g2o, graph-based slam, qualityAssured, rank1},
  owner          = {y},
  timestamp      = {2014.04.27},
}

@Article{Kwon2013,
  author         = {Kwon, H. and Yousef, K. M. A. and Kak, A. C.},
  title          = {Building 3D visual maps of interior space with a new hierarchical sensor fusion architecture},
  journal        = {Robotics and Autonomous Systems},
  year           = {2013},
  volume         = {61},
  number         = {8},
  pages          = {749--767},
  issn           = {0921-8890},
  comment        = {14.10.27 Range+Camera进行Fusion的工作�?? 亮点：map既有2d的精确�?�，亦有3d的纹理图案�?? 缺点：只提竖直平面，表达复杂的场景会有困难�?? 地图基本不带有语义信息�?? �????????????有使用fusion的方法对机器人传感器的要求都较为苛刻。},
  file           = {Kwon2013.pdf:Kwon2013.pdf:PDF},
  keywords       = {Sensor fusion Hierarchical map building SLAM Dense visual map simultaneous localization mobile robot loop closure environment vision slam extraction navigation framework features, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Labbe2013,
  Title                    = {Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation},
  Author                   = {Labbe, M. and Michaud, F.},
  Journal                  = {IEEE Transactions on Robotics},
  Year                     = {2013},
  Number                   = {3},
  Pages                    = {734--745},
  Volume                   = {29},

  File                     = {Published version:Labbe2013.pdf:PDF},
  ISSN                     = {1552-3098},
  Keywords                 = {loop closure,},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@InProceedings{Labbe2014,
  author       = {Labb{\'e}, Mathieu and Michaud, Fran{\c{c}}ois},
  title        = {Online global loop closure detection for large-scale multi-session graph-based slam},
  booktitle    = {2014 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year         = {2014},
  pages        = {2661--2666},
  organization = {IEEE},
  owner        = {cyang},
  timestamp    = {2016.10.11},
}

@InProceedings{Lai2012,
  Title                    = {Detection-based object labeling in 3d scenes},
  Author                   = {Lai, Kevin and Bo, Liefeng and Ren, Xiaofeng and Fox, Dieter},
  Booktitle                = {Robotics and Automation (ICRA), 2012 IEEE International Conference on},
  Year                     = {2012},
  Organization             = {IEEE},
  Pages                    = {1330--1337},

  Owner                    = {x},
  Timestamp                = {2015.05.22}
}

@InCollection{Lategahn2011,
  Title                    = {Visual SLAM for Autonomous Ground Vehicles},
  Author                   = {Lategahn, Henning and Geiger, Andreas and Kitt, Bernd},
  Year                     = {2011},
  Pages                    = {1732--1737},

  File                     = {Published version:Lategahn2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Lategahn2014,
  Title                    = {Vision-Only Localization},
  Author                   = {Lategahn, H. and Stiller, C.},
  Journal                  = {Intelligent Transportation Systems, IEEE Transactions on},
  Year                     = {2014},

  Month                    = {June},
  Number                   = {3},
  Pages                    = {1246-1257},
  Volume                   = {15},

  Doi                      = {10.1109/TITS.2014.2298492},
  ISSN                     = {1524-9050},
  Keywords                 = {Global Positioning System;SLAM (robots);augmented reality;feature extraction;graph theory;image sequences;intelligent transportation systems;object detection;optimisation;pose estimation;real-time systems;rendering (computer graphics);road vehicles;robot vision;sensor placement;stereo image processing;video cameras;AR system;GNSS;accurate metric pose;augmented reality system;automatic map ingredient extraction;autonomous vehicles;centimeter level accuracy;degrees-of-freedom ego localization;ego pose recovery;factor graph optimization process;global navigation satellite systems;global positioning sensor;global scene signatures;intelligent vehicles;local landmark descriptors;localization algorithm;mapping trajectory;metric localization;metric refinement;monocular camera;multipath propagation rendering;real-time system;stereoscopic image sequences;topological localization;urban environment;vision-only localization;Accuracy;Cameras;Global Positioning System;Trajectory;Vectors;Vehicles;Visualization;Bundle adjustment;camera;global positioning system (GPS);landmark;localization;nonlinear least squares (NLS);simultaneous localization and mapping (SLAM)},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Latif2013,
  author         = {Latif, Yasir and Cadena, C{\'{e}}sar and Neira, Jos{\'{e}}},
  title          = {Robust loop closing over time for pose graph SLAM},
  journal        = {The International Journal of Robotics Research},
  year           = {2013},
  volume         = {32},
  number         = {14},
  pages          = {1611--1626},
  __markedentry  = {[x:]},
  abstract       = {Long-term autonomous mobile robot operation requires considering place recognition decisions with great caution. A single incorrect decision that is not detected and reconsidered can corrupt the environment model that the robot is trying to build and maintain. This work describes a consensus-based approach to robust place recognition over time, that takes into account all the available information to detect and remove past incorrect loop closures. The main novelties of our work are: (1) the ability of realizing that, in light of new evidence, an incorrect past loop closing decision has been made; the incorrect information can be removed thus recovering the correct estimation with a novel algorithm; (2) extending our proposal to incremental operation; and (3) handling multi-session, spatially related or unrelated scenarios in a unified manner. We demonstrate our proposal, the RRR algorithm, on different odometry systems, e.g. visual or laser, using different front-end loop-closing techniques. For our experiments we use the efficient graph optimization framework g2o as back-end. We back our claims up with several experiments carried out on real data, in single and multi-session experiments showing better results than those obtained by state-of-the-art methods, comparisons against whom are also presented.},
  comment        = {14.11.25 可以从作者的主页下载代码，代码很清晰�???????????? 文章提出的方法叫RRR：Realizing, Reversing, Recovering.该算法对BoW提出的loop进行验证。它�????????????测g2o图中是否有不�????????????致的loop，然后尝试去除它们�?�},
  file           = {Latif2013.pdf:pdf/Latif2013.pdf:PDF},
  keywords       = {qualityAssured, rank4},
  owner          = {y},
  timestamp      = {2014.08.24},
}

@Article{Lee2011,
  Title                    = {Robust RBPF-SLAM for Indoor Mobile Robots Using Sonar Sensors in Non-Static Environments},
  Author                   = {Lee, J. S. and Nam, S. Y. and Chung, W. K.},
  Journal                  = {Advanced Robotics},
  Year                     = {2011},
  Number                   = {9-10},
  Pages                    = {1227--1248},
  Volume                   = {25},

  ISSN                     = {0169-1864},
  Keywords                 = {RBPF-SLAM non-static environment mobile robot particle filtering localization},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Lee2013,
  Title                    = {Performance Improvement of Iterative Closest Point-Based Outdoor SLAM by Rotation Invariant Descriptors of Salient Regions},
  Author                   = {Lee, Yong-Ju and Song, Jae-Bok and Choi, Ji-Hoon},
  Journal                  = {Journal of Intelligent \& Robotic Systems},
  Year                     = {2013},
  Number                   = {3-4},
  Pages                    = {349--360},
  Volume                   = {71},

  File                     = {Published version:Lee2013.pdf:PDF},
  ISSN                     = {0921-0296},
  Keywords                 = {Mapping; SLAM; Iterative closest point (ICP); 3-D maps; Outdoor navigation},
  Language                 = {English},
  Owner                    = {y},
  Publisher                = {Springer Netherlands},
  Timestamp                = {2014.08.25}
}

@Article{Lee2014,
  Title                    = {Solution to the SLAM Problem in Low Dynamic Environments Using a Pose Graph and an RGB-D Sensor},
  Author                   = {Lee, D. and Myung, H.},
  Journal                  = {Sensors},
  Year                     = {2014},
  Number                   = {7},
  Pages                    = {12467--12496},
  Volume                   = {14},

  File                     = {Lee2014.pdf:Lee2014.pdf:PDF},
  ISSN                     = {1424-8220},
  Keywords                 = {simultaneous localization and mapping (SLAM) low dynamic environment pose graph RGB-D (red-green-blue depth) localization},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Lee2014a,
  Title                    = {SLAM with SC-PHD Filters: An Underwater Vehicle Application},
  Author                   = {Chee Sing Lee and Nagappa, S. and Palomeras, N. and Clark, D.E. and Salvi, J.},
  Journal                  = {Robotics Automation Magazine, IEEE},
  Year                     = {2014},

  Month                    = {June},
  Number                   = {2},
  Pages                    = {38-45},
  Volume                   = {21},

  Doi                      = {10.1109/MRA.2014.2310132},
  ISSN                     = {1070-9932},
  Keywords                 = {SLAM (robots);autonomous underwater vehicles;filtering theory;mobile robots;object detection;probability;sensor fusion;state estimation;target tracking;SC-PHD filters;SLAM;cluttered environments;feature-based simultaneous localization and mapping;hierarchical multiobject estimation method;landmark estimation;mathematical framework;mobile robotics;multiple-target tracking algorithms;random finite-set formulation;sensor fusion;single cluster-probability hypothesis density filter;underwater vehicle application;unified probabilistic framework;vehicle position estimation;Automation;Estimation;Object tracking;Simultaneous localization and mapping;Underwater vehicles;Weight measurement},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Lee2015,
  Title                    = {DV-SLAM (Dual-Sensor-Based Vector-Field SLAM) and Observability Analysis},
  Author                   = {Seung-Mok Lee and Jongdae Jung and Shin Kim and In-Joo Kim and Hyun Myung},
  Journal                  = {Industrial Electronics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {Feb},
  Number                   = {2},
  Pages                    = {1101-1112},
  Volume                   = {62},

  Doi                      = {10.1109/TIE.2014.2341595},
  ISSN                     = {0278-0046},
  Keywords                 = {SLAM (robots);interpolation;magnetic field measurement;magnetic sensors;matrix algebra;mobile robots;observability;particle filtering (numerical methods);path planning;DV-SLAM;Earth magnetic field sensors;FIM;Fisher information matrix;Observability Analysis;RBPF;Rao-Blackwellized particle filter;bilinear interpolation;dual-sensor-based vector-field SLAM;fixed heading;mobile robot;performance improvement;robot motion;sensor measurements;vector field signal measurement;vector field simultaneous localization and mapping;Interpolation;Observability;Service robots;Simultaneous localization and mapping;Vectors;Dual sensor;Rao???Blackwellized particle filter (RBPF);simultaneous localization and mapping (SLAM);vector-field SLAM},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Lenz2015,
  Title                    = {Deep learning for detecting robotic grasps},
  Author                   = {Lenz, Ian and Lee, Honglak and Saxena, Ashutosh},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2015},
  Number                   = {4-5},
  Pages                    = {705--724},
  Volume                   = {34},

  Owner                    = {x},
  Publisher                = {SAGE Publications},
  Timestamp                = {2015.12.14}
}

@Article{Lepetit2006,
  Title                    = {Keypoint recognition using randomized trees},
  Author                   = {Lepetit, Vincent and Fua, Pascal},
  Journal                  = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  Year                     = {2006},
  Number                   = {9},
  Pages                    = {1465--1479},
  Volume                   = {28},

  Owner                    = {zero},
  Publisher                = {IEEE},
  Timestamp                = {2015.04.09}
}

@Article{LepetitMoreno-NoguerFua2008,
  author =   {Lepetit, Vincent and Moreno-Noguer, Francesc and Fua, Pascal},
  title =    {EPnP: An Accurate O(n) Solution to the PnP Problem},
  journal =  {International Journal of Computer Vision},
  year =     {2008},
  volume =   {81},
  number =   {2},
  pages =    {155--166},
  abstract = {We propose a non-iterative solution to the PnP problem---the estimation of the pose of a calibrated camera from n 3D-to-2D point correspondences---whose computational complexity grows linearly with n. This is in contrast to state-of-the-art methods that are O(n                        5) or even O(n                        8), without being more accurate. Our method is applicable for all n≥4 and handles properly both planar and non-planar configurations. Our central idea is to express the n 3D points as a weighted sum of four virtual control points. The problem then reduces to estimating the coordinates of these control points in the camera referential, which can be done in O(n) time by expressing these coordinates as weighted sum of the eigenvectors of a 12{\texttimes}12 matrix and solving a small constant number of quadratic equations to pick the right weights. Furthermore, if maximal precision is required, the output of the closed-form solution can be used to initialize a Gauss-Newton scheme, which improves accuracy with negligible amount of additional time. The advantages of our method are demonstrated by thorough testing on both synthetic and real-data.},
  doi =      {10.1007/s11263-008-0152-6},
  issn =     {1573-1405},
  url =      {http://dx.doi.org/10.1007/s11263-008-0152-6}
}

@InProceedings{Li2006,
  author       = {Li, Hongdong and Hartley, Richard},
  title        = {Five-point motion estimation made easy},
  booktitle    = {18th International Conference on Pattern Recognition (ICPR'06)},
  year         = {2006},
  volume       = {1},
  pages        = {630--633},
  organization = {IEEE},
}

@InProceedings{Li2012,
  author =         {Li, Gang and Zhu, Chun and Du, Jianhao and Cheng, Qi and Sheng, Weihua and Chen, Heping},
  title =          {Robot semantic mapping through wearable sensor-based human activity recognition},
  booktitle =      {Robotics and Automation (ICRA), 2012 IEEE International Conference on},
  year =           {2012},
  pages =          {5228--5233},
  organization =   {IEEE},
  file =           {Published version:Li2012.pdf:PDF},
  keywords =       {qualityAssured, rank3},
  owner =          {GaoXiang},
  timestamp =      {2014.01.13}
}

@Article{Lim2012,
  Title                    = {Online environment mapping using metric-topological maps},
  Author                   = {Lim, J. and Frahm, J. M. and Pollefeys, M.},
  Journal                  = {International Journal of Robotics Research},
  Year                     = {2012},
  Number                   = {12},
  Pages                    = {1394--1408},
  Volume                   = {31},

  ISSN                     = {0278-3649},
  Keywords                 = {Visual SLAM Metric-topological mapping Bundle adjustment Optimization Scalability bundle adjustment nested dissection slam camera},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Liou2014,
  author    = {Liou, Cheng-Yuan and Cheng, Wei-Chen and Liou, Jiun-Wei and Liou, Daw-Ran},
  title     = {Autoencoder for words},
  journal   = {Neurocomputing},
  year      = {2014},
  volume    = {139},
  pages     = {84--96},
  comment   = {Autoencoder},
  file      = {Liou2014.pdf:Liou2014.pdf:PDF},
  keywords  = {rank3},
  owner     = {x},
  publisher = {Elsevier},
  timestamp = {2014.12.17},
}

@Article{Liu2014,
  author         = {Liu, M. and Siegwart, R.},
  title          = {Topological Mapping and Scene Recognition With Lightweight Color Descriptors for an Omnidirectional Camera},
  journal        = {IEEE Transactions on Robotics},
  year           = {2014},
  volume         = {30},
  number         = {2},
  pages          = {310--324},
  issn           = {1552-3098},
  comment        = {14.10.20 介绍了全景相机的�??????????个SLAM应用。建拓扑地图。工作分为两个部分： 1. 图像处理。对全景相机的图像进行分割，然后提取�??????????种novel的彩色图像特征�?�观点：常见的特征基本都很费时间，但是彩色图像特征容易受光照影响，特别是在rgb空间。作者的特征是在yuv空间中提取的�?????????? 2. 地图方向用了Dirichlet process mixture model，不太看得懂�???????????? 作�?�的观点�???????????? 1. 地图分为metric map和topological map两种，前者较精确，可直接用于导航，但是信息比较的冗余，not capable of handling the data in an efficient way. 后�?�接近于人的思维，表示机器人对环境的�????????????种理解，可应用于高级的人机交互�??2. visual SLAM中的特征提取通常很费时间。},
  file           = {Liu2014.pdf:Liu2014.pdf:PDF},
  keywords       = {Graphic model non-parametric learning omnidirectional camera scene recognition topological segmentation monte-carlo localization mobile robot navigation map features images slam representations classification integration appearance, rank4, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Liu2014a,
  Title                    = {Automatic objects segmentation with RGB-D cameras},
  Author                   = {Liu, Haowei and Philipose, Matthai and Sun, Ming-Ting},
  Journal                  = {Journal of Visual Communication and Image Representation},
  Year                     = {2014},
  Number                   = {4},
  Pages                    = {709--718},
  Volume                   = {25},

  File                     = {Liu2014a.pdf:Liu2014a.pdf:PDF},
  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.26}
}

@Article{Liu2016,
  author =  {Liu Haomin and Zhang Guofeng and Bao Hujun},
  title =   {A Survey of Monocular Simultaneous Localization and Mapping},
  journal = {Journal of Computer-Aided Design and Compute Graphics},
  year =    {2016},
  volume =  {28},
  number =  {6},
  pages =   {855--868},
  note =    {in Chinese},
  lang =    {chinese}
}

@Article{Lloyd1982,
  author    = {Lloyd, Stuart},
  title     = {Least squares quantization in PCM},
  journal   = {IEEE transactions on information theory},
  year      = {1982},
  volume    = {28},
  number    = {2},
  pages     = {129--137},
  owner     = {cyang},
  publisher = {IEEE},
  timestamp = {2016.10.01},
}

@Article{Loncomilla2012,
  Title                    = {Visual SLAM Based on Rigid-Body 3D Landmarks},
  Author                   = {Loncomilla, Patricio and Ruiz Del Solar, Javier},
  Journal                  = {Journal of Intelligent and Robotic Systems},
  Year                     = {2012},
  Number                   = {1-2SI},
  Pages                    = {125--149},
  Volume                   = {66},

  File                     = {Loncomilla2012.pdf:Loncomilla2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Long2014,
  author =         {Long, Jonathan and Shelhamer, Evan and Darrell, Trevor},
  title =          {Fully convolutional networks for semantic segmentation},
  journal =        {arXiv preprint arXiv:1411.4038},
  year =           {2014},
  file =           {Long2014.pdf:Long2014.pdf:PDF},
  keywords =       {rank5, qualityAssured},
  owner =          {x},
  timestamp =      {2015.11.10}
}

@Article{Lourakis2009,
  Title                    = {SBA: A software package for generic sparse bundle adjustment},
  Author                   = {Lourakis, Manolis IA and Argyros, Antonis A},
  Journal                  = {ACM Transactions on Mathematical Software (TOMS)},
  Year                     = {2009},
  Number                   = {1},
  Pages                    = {2},
  Volume                   = {36},

  Owner                    = {x},
  Publisher                = {ACM},
  Timestamp                = {2014.12.09}
}

@Article{Lowe2004,
  author         = {Lowe, David G},
  title          = {Distinctive image features from scale-invariant keypoints},
  journal        = {International Journal of Computer Vision},
  year           = {2004},
  volume         = {60},
  number         = {2},
  pages          = {91--110},
  comment        = {�????????????早提出SIFT特征的文章，Lowe大大的�?�},
  file           = {Lowe2004.pdf:/home/x3/bib/pdf/Lowe2004.pdf:PDF},
  keywords       = {SIFT, feature, qualityAssured, rank5},
  owner          = {x},
  publisher      = {Springer},
  timestamp      = {2014.09.08},
}

@InProceedings{Lu2013,
  Title                    = {Speech enhancement based on deep denoising autoencoder.},
  Author                   = {Lu, Xugang and Tsao, Yu and Matsuda, Shigeki and Hori, Chiori},
  Booktitle                = {INTERSPEECH},
  Year                     = {2013},
  Pages                    = {436--440},

  Owner                    = {x},
  Timestamp                = {2015.09.13}
}

@Article{Lu2015,
  Title                    = {Visual Navigation Using Heterogeneous Landmarks and Unsupervised Geometric Constraints},
  Author                   = {Yan Lu and Dezhen Song},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {June},
  Number                   = {3},
  Pages                    = {736-749},
  Volume                   = {31},

  Doi                      = {10.1109/TRO.2015.2424032},
  ISSN                     = {1552-3098},
  Keywords                 = {SLAM (robots);feature extraction;graph theory;mobile robots;navigation;path planning;robot vision;unsupervised learning;KITTI dataset;MFG;heterogeneous landmark-based visual navigation approach;heterogeneous visual features;inner geometric constraints;local bundle adjustment-based visual simultaneous localization and mapping framework;monocular mobile robot;multilayer feature graph;multiple indoor datasets;multiple outdoor datasets;point landmark-based visual SLAM methods;unsupervised geometric constraints;Cameras;Feature extraction;Navigation;Robot vision systems;Simultaneous localization and mapping;Visualization;Heterogeneous landmarks;simultaneous localization and mapping (SLAM);visual navigation},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Lui2012,
  Title                    = {A pure vision-based topological {SLAM} system},
  Author                   = {Lui, Wen Lik Dennis and Jarvis, Ray},
  Journal                  = {International Journal Of Robotics Research},
  Year                     = {2012},
  Number                   = {4SI},
  Pages                    = {403--428},
  Volume                   = {31},

  __markedentry            = {[y:5]},
  File                     = {Published version:Lui2012.pdf:PDF},
  Keywords                 = {vision SLAM, topological, important, FAB-MAP, appearance-based, PR},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Luo2012,
  Title                    = {Concurrent Indoor Map Construction and Patterns of Interests Recognition Using Sensory Fusion Approach for Service Robotics},
  Author                   = {Luo, Ren C. and Lai, Chun C.},
  Journal                  = {2012 IEEE International Conference On Robotics And Automation (ICRA)},
  Year                     = {2012},
  Pages                    = {2243--2248},

  File                     = {Published version:Luo2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Luo2014,
  Title                    = {Multisensor Fusion-Based Concurrent Environment Mapping and Moving Object Detection for Intelligent Service Robotics},
  Author                   = {Luo, R.C. and Chun Chi Lai},
  Journal                  = {Industrial Electronics, IEEE Transactions on},
  Year                     = {2014},

  Month                    = {Aug},
  Number                   = {8},
  Pages                    = {4043-4051},
  Volume                   = {61},

  Doi                      = {10.1109/TIE.2013.2288199},
  ISSN                     = {0278-0046},
  Keywords                 = {SLAM (robots);graph theory;image fusion;image motion analysis;intelligent robots;mobile robots;object detection;path planning;pose estimation;robot kinematics;robot vision;service robots;association efficiency enhancement;concurrent robot posture estimation;concurrent simultaneous localization-and-mapping;consistent association problem;covariance area intersection belief assignment;graph-based optimal estimation;human community applications;indoor navigation;intelligent service robot development;intelligent service robotics;kinematics;motion state evaluation;moving object detection;moving object trajectory estimation;multisensor fusion-based concurrent environment mapping;synergistic multiple sensor fusion;vision features;Cameras;Estimation;Laser fusion;Measurement by laser beam;Simultaneous localization and mapping;Stereo vision;Concurrent simultaneous localization and mapping (SLAM) and moving object detection;environment perception;multisensor fusion},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Maddern2012,
  author        = {Maddern, Will and Milford, Michael and Wyeth, Gordon},
  title         = {CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory},
  journal       = {International Journal of Robotics Research},
  year          = {2012},
  volume        = {31},
  number        = {4SI},
  pages         = {429--451},
  __markedentry = {[y:5]},
  file          = {Published version:Maddern2012.pdf:PDF},
  keywords      = {collabrative slam, dynamic, important},
  owner         = {GaoXiang},
  timestamp     = {2014.01.13},
}
@phdthesis{malis2007deeper,
title={Deeper understanding of the homography decomposition for vision-based control},
author={Malis, Ezio and Vargas, Manuel},
year={2007},
school={INRIA}
}

@Article{Maohai2013,
  Title                    = {An efficient {SLAM} system only using RGBD sensors},
  Author                   = {Maohai, Li and Rui, Lin and Han, Wang and Hui, Xu},
  Journal                  = {2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)},
  Year                     = {2013},
  Pages                    = {1653--8},

  __markedentry            = {[y:1]},
  File                     = {Published version:Maohai2013.pdf:PDF},
  Keywords                 = {rgb-d slam, ceiling,},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.04.19}
}

@Article{Marin2014,
  Title                    = {Event-Based Localization in Ackermann Steering Limited Resource Mobile Robots},
  Author                   = {Marin, L. and Valles, M. and Soriano, A. and Valera, A. and Albertos, P.},
  Journal                  = {Mechatronics, IEEE/ASME Transactions on},
  Year                     = {2014},

  Month                    = {Aug},
  Number                   = {4},
  Pages                    = {1171-1182},
  Volume                   = {19},

  Doi                      = {10.1109/TMECH.2013.2277271},
  ISSN                     = {1083-4435},
  Keywords                 = {Global Positioning System;Kalman filters;SLAM (robots);cameras;covariance matrices;mobile robots;pose estimation;position control;position measurement;sensor fusion;Ackermann steering limited resource mobile robots;Ackermann steering mobile robot local dynamic model;Kalman filter error covariance;LEGO Mindstorm NXT robot;event-based global position correction;event-based localization;global sensor;limited computational resources;local sensor fusion technique;mobile robot localization improvement;modified Kalman filter;position measurement;zenithal camera;Estimation;Global Positioning System;Mobile robots;Robot kinematics;Robot sensing systems;Wheels;Dynamic model;Kalman filtering;embedded systems;event-based systems;global positioning systems (GPSs);inertial sensors;mobile robots;pose estimation;position measurement;robot sensing systems;sensor fusion},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Martin2004,
  Title                    = {Learning to detect natural image boundaries using local brightness, color, and texture cues},
  Author                   = {Martin, David R and Fowlkes, Charless C and Malik, Jitendra},
  Journal                  = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  Year                     = {2004},
  Number                   = {5},
  Pages                    = {530--549},
  Volume                   = {26},

  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.08.31}
}

@Article{Martinelli2014,
  Title                    = {Closed-Form Solution of Visual-Inertial Structure from Motion},
  Author                   = {Martinelli, Agostino},
  Journal                  = {International Journal of Computer Vision},
  Year                     = {2014},
  Number                   = {2},
  Pages                    = {138--152},
  Volume                   = {106},

  File                     = {Published version:Martinelli2014.pdf:PDF},
  ISSN                     = {0920-5691},
  Keywords                 = {Sensor fusion; Structure from motion; Inertial sensors; Robotics},
  Language                 = {English},
  Owner                    = {y},
  Publisher                = {Springer US},
  Timestamp                = {2014.08.25}
}

@InProceedings{Martinez-Carranza2010,
  Title                    = {Unifying Planar and Point Mapping in Monocular SLAM.},
  Author                   = {Mart{\'\i}nez-Carranza, Jos{\'e} and Calway, Andrew},
  Booktitle                = {BMVC},
  Year                     = {2010},
  Organization             = {Citeseer},
  Pages                    = {1--11},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@InCollection{Mason2012,
  Title                    = {Object Disappearance for Object Discovery},
  Author                   = {Mason, Julian and Marthi, Bhaskara and Parr, Ronald},
  Year                     = {2012},
  Pages                    = {2836--2843},

  File                     = {Published version:Mason2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{McClelland2014,
  Title                    = {Qualitative Relational Mapping for Mobile Robots with Minimal Sensing},
  Author                   = {McClelland, M. and Campbell, M. and Estlin, T.},
  Journal                  = {Journal of Aerospace Information Systems},
  Year                     = {2014},
  Number                   = {8},
  Pages                    = {497--511},
  Volume                   = {11},

  ISSN                     = {1940-3151},
  Keywords                 = {simultaneous localization navigation slam information map consistency orientation space},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Meger2008,
  Title                    = {Curious george: An attentive semantic robot},
  Author                   = {Meger, David and Forss{\'e}n, Per-Erik and Lai, Kevin and Helmer, Scott and McCann, Sancho and Southey, Tristram and Baumann, Matthew and Little, James J and Lowe, David G},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2008},
  Number                   = {6},
  Pages                    = {503--511},
  Volume                   = {56},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.25}
}

@InProceedings{Mei2008,
  Title                    = {Modeling and generating complex motion blur for real-time tracking},
  Author                   = {Mei, Christopher and Reid, Ian},
  Booktitle                = {Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on},
  Year                     = {2008},
  Organization             = {IEEE},
  Pages                    = {1--8},

  Owner                    = {x},
  Timestamp                = {2015.05.17}
}

@Article{Mei2011,
  Title                    = {RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo},
  Author                   = {Mei, C. and Sibley, G. and Cummins, M. and Newman, P. and Reid, I.},
  Journal                  = {International Journal of Computer Vision},
  Year                     = {2011},
  Number                   = {2},
  Pages                    = {198--214},
  Volume                   = {94},

  ISSN                     = {0920-5691},
  Keywords                 = {SLAM Stereo Tracking Loop closing SIFT localization map},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@InCollection{Mei2012,
  Title                    = {Robust and Accurate Pose Estimation for Vision-based Localisation},
  Author                   = {Mei, Christopher},
  Year                     = {2012},
  Pages                    = {3165--3170},

  File                     = {Published version:Mei2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Mesnil2012,
  Title                    = {Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.},
  Author                   = {Mesnil, Gr{\'e}goire and Dauphin, Yann and Glorot, Xavier and Rifai, Salah and Bengio, Yoshua and Goodfellow, Ian J and Lavoie, Erick and Muller, Xavier and Desjardins, Guillaume and Warde-Farley, David and others},
  Journal                  = {ICML Unsupervised and Transfer Learning},
  Year                     = {2012},
  Pages                    = {97--110},
  Volume                   = {27},

  Owner                    = {x},
  Timestamp                = {2015.09.13}
}

@InCollection{Mihalyi2013,
  Title                    = {Uncertainty Estimation of AR-Marker Poses for Graph-{SLAM} Optimization in 3D Object Model Generation with RGBD Data},
  Author                   = {Mihalyi, Razvan-George and Pathak, Kaustubh and Vaskevicius, Narunas and Birk, Andreas},
  Year                     = {2013},
  Pages                    = {1807--1813},

  File                     = {Published version:Mihalyi2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.04.19}
}

@Article{Mikolajczyk2005,
  Title                    = {A comparison of affine region detectors},
  Author                   = {Mikolajczyk, Krystian and Tuytelaars, Tinne and Schmid, Cordelia and Zisserman, Andrew and Matas, Jiri and Schaffalitzky, Frederik and Kadir, Timor and Van Gool, Luc},
  Journal                  = {International journal of computer vision},
  Year                     = {2005},
  Number                   = {1-2},
  Pages                    = {43--72},
  Volume                   = {65},

  Owner                    = {x},
  Publisher                = {Springer},
  Timestamp                = {2015.05.18}
}

@Article{Milford2008,
  Title                    = {Mapping a suburb with a single camera using a biologically inspired SLAM system},
  Author                   = {Milford, Michael J and Wyeth, Gordon F},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2008},
  Number                   = {5},
  Pages                    = {1038--1053},
  Volume                   = {24},

  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.05.17}
}

@Article{Milford2012,
  Title                    = {SeqSLAM: Visual Route-Based Navigation for Sunny Summer Days and Stormy Winter Nights},
  Author                   = {Milford, Michael J. and Wyeth, Gordon. F.},
  Journal                  = {2012 IEEE International Conference On Robotics And Automation (ICRA)},
  Year                     = {2012},
  Pages                    = {1643--1649},

  File                     = {Published version:Milford2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Milford2013,
  Title                    = {Vision-based place recognition: how low can you go?},
  Author                   = {Milford, Michael},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {7},
  Pages                    = {766--789},
  Volume                   = {32},

  Abstract                 = {In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.},
  Eprint                   = {http://ijr.sagepub.com/content/32/7/766.full.pdf+html},
  File                     = {Published version:Milford2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@InProceedings{Mishra2012,
  Title                    = {Segmenting “simple" objects using RGB-D},
  Author                   = {Mishra, Ajay K and Shrivastava, Ashish and Aloimonos, Yiannis},
  Booktitle                = {Robotics and Automation (ICRA), 2012 IEEE International Conference on},
  Year                     = {2012},
  Organization             = {IEEE},
  Pages                    = {4406--4413},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@InProceedings{Modayil2004,
  Title                    = {Bootstrap learning for object discovery},
  Author                   = {Modayil, Joseph and Kuipers, Benjamin},
  Booktitle                = {Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on},
  Year                     = {2004},
  Organization             = {IEEE},
  Pages                    = {742--747},
  Volume                   = {1},

  Owner                    = {x},
  Timestamp                = {2015.05.22}
}

@Article{Moeller2013,
  Title                    = {Cleaning robot navigation using panoramic views and particle clouds as landmarks},
  Author                   = {Ralf M{\"{o}}ller and Martin Krzykawski and Lorenz Gerstmayr-Hillen and Michael Horst and David Fleer and Janina de Jong},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2013},
  Number                   = {12},
  Pages                    = {1415--1439},
  Volume                   = {61},

  Abstract                 = {Abstract The paper describes a visual method for the navigation of autonomous floor-cleaning robots. The method constructs a topological map with metrical information where place nodes are characterized by panoramic images and by particle clouds representing position estimates. Current image and position estimate of the robot are interrelated to landmark images and position estimates stored in the map nodes through a holistic visual homing method which provides bearing and orientation estimates. Based on these estimates, a position estimate of the robot is updated by a particle filter. The robot{\textquoteright}s position estimates are used to guide the robot along parallel, meandering lanes and are also assigned to newly created map nodes which later serve as landmarks. Computer simulations and robot experiments confirm that the robot position estimate obtained by this method is sufficiently accurate to keep the robot on parallel lanes, even in the presence of large random and systematic odometry errors. This ensures an efficient cleaning behavior with almost complete coverage of a rectangular area and only small repeated coverage. Furthermore, the topological-metrical map can be used to completely cover rooms or apartments by multiple meander parts. },
  File                     = {Published version:Moeller2013.pdf:PDF},
  ISSN                     = {0921-8890},
  Keywords                 = {Cleaning robot},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Mohedano2014,
  Title                    = {Camera Localization Using Trajectories and Maps},
  Author                   = {Mohedano, R. and Cavallaro, A and Garcia, N.},
  Journal                  = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  Year                     = {2014},

  Month                    = {\#apr\#},
  Number                   = {4},
  Pages                    = {684--697},
  Volume                   = {36},

  File                     = {Published version:Mohedano2014.pdf:PDF},
  ISSN                     = {0162-8828},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@InProceedings{Montemerlo2002,
  author                     = {Montemerlo, M and Thrun, S and Koller, D and Wegbreit, B},
  title                      = {FastSLAM: A factored solution to the simultaneous localization and mapping problem},
  booktitle                  = {Eighteenth National Conference On Artificial Intelligence (AAAI-02)},
  year                       = {2002},
  pages                      = {593--598},
  publisher                  = {MIT PRESS},
  book-group-author          = {{AAAI AAAI}},
  comment                    = {FastSLAM的开山之作�?? 虽然自己不太清楚FastSLAM具体是�?�么回事。�?��?�},
  doc-delivery-number        = {{BW91S}},
  isbn                       = {{0-262-51129-0}},
  keywords                   = {qualityAssured, rank5},
  language                   = {{English}},
  number-of-cited-references = {{18}},
  owner                      = {zero},
  research-areas             = {{Computer Science}},
  times-cited                = {{24}},
  timestamp                  = {2014.10.16},
  unique-id                  = {{ISI:000183593700089}},
  web-of-science-categories  = {{Computer Science, Artificial Intelligence}},
}

@Article{Montero2012,
  Title                    = {Framework for Natural Landmark-based Robot Localization},
  Author                   = {Montero, A. S. and Sekkati, H. and Jochen, Lang and Laganiere, R. and James, J.},
  Journal                  = {2012 Canadian Conference on Computer and Robot Vision},
  Year                     = {2012},
  Pages                    = {131--8},

  __markedentry            = {[y:1]},
  File                     = {Published version:Montero2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Montiel2006,
  author  = {Montiel, JMM and Civera, Javier and Davison, Andrew J},
  title   = {Unified inverse depth parametrization for monocular SLAM},
  journal = {analysis},
  year    = {2006},
  volume  = {9},
  pages   = {1},
}

@Article{Moratuwage2014,
  Title                    = {RFS Collaborative Multivehicle SLAM: SLAM in Dynamic High-Clutter Environments},
  Author                   = {Moratuwage, D. and Danwei Wang and Rao, A. and Senarathne, N. and Han Wang},
  Journal                  = {Robotics Automation Magazine, IEEE},
  Year                     = {2014},

  Month                    = {June},
  Number                   = {2},
  Pages                    = {53-59},
  Volume                   = {21},

  Doi                      = {10.1109/MRA.2014.2312841},
  ISSN                     = {1070-9932},
  Keywords                 = {SLAM (robots);estimation theory;particle filtering (numerical methods);probability;sensor fusion;set theory;CMSLAM problem;PHD filter-based landmark map posterior estimation;RFS SLAM filter framework;RFS collaborative multivehicle SLAM;Rao-Blackwellized particle filter-based vehicle trajectories posterior estimation;collaborative multivehicle simultaneous localization and mapping problem;dynamic high-clutter environment;finite set statistics;high-clutter environmental condition;multisensor information fusion technique;performance evaluation;probability hypothesis density filter-based landmark map posterior estimation;random finite set SLAM filter framework;vehicle trajectory;Clutter approximation;Intelligent vehicles;Mobile radio mobility management;Object tracking;Simultaneous localization and mapping;Time measurement;Trajectory},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Morell-Gimenez2014,
  author         = {Morell-Gimenez, V. and Saval-Calvo, M. and Azorin-Lopez, J. and Garcia-Rodriguez, J. and Cazorla, M. and Orts-Escolano, S. and Fuster-Guillo, A.},
  title          = {A Comparative Study of Registration Methods for RGB-D Video of Static Scenes},
  journal        = {Sensors},
  year           = {2014},
  volume         = {14},
  number         = {5},
  pages          = {8547--8576},
  issn           = {1424-8220},
  comment        = {14.10.30 在Strum的数据集上，对比了几种方法： 1.feature(FAST+BRIEF)+RANSAC 2.Dense visual odometry(ROS). 3.Kinect Fusion. 4.feature+ICP 5.ICP 结论是Dvo的效果最好，在准确和鲁棒性上均有较好表现。},
  file           = {Morell-Gimenez2014.pdf:Morell-Gimenez2014.pdf:PDF},
  keywords       = {RGB-D sensor registration robotics mapping object reconstruction random sample consensus image registration 3d tracking robust recognition accuracy features slam, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Morioka2011,
  Title                    = {Vision-based Mobile Robot's SLAM and Navigation in Crowded Environments},
  Author                   = {Morioka, Hiroshi and Yi, Sangkyu and Hasegawa, Osamu},
  Journal                  = {2011 IEEE/rsj International Conference On Intelligent Robots And Systems},
  Year                     = {2011},
  Pages                    = {3998--4005},

  File                     = {Published version:Morioka2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Morioka2014,
  author         = {Morioka, K. and Yamanaka, S. and Hoshino, F.},
  title          = {Simplified map representation and map learning system for autonomous navigation of mobile robots},
  journal        = {Intelligent Service Robotics},
  year           = {2014},
  volume         = {7},
  number         = {1},
  pages          = {25--35},
  issn           = {1861-2776},
  comment        = {14.10.24 又是�????????????个做地图表示的�?? 怎么感觉有点水水的样子呢？},
  file           = {Morioka2014.pdf:Morioka2014.pdf:PDF},
  keywords       = {Mobile robot SLAM Navigation localization, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Mozos2007,
  Title                    = {Supervised semantic labeling of places using information extracted from sensor data},
  Author                   = {Mozos, Oscar Martinez and Triebel, Rudolph and Jensfelt, Patric and Rottmann, Axel and Burgard, Wolfram},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2007},
  Number                   = {5},
  Pages                    = {391--402},
  Volume                   = {55},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.22}
}

@InProceedings{Muja2009,
  Title                    = {Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration.},
  Author                   = {Muja, Marius and Lowe, David G},
  Booktitle                = {VISAPP (1)},
  Year                     = {2009},
  Pages                    = {331--340},

  Owner                    = {x},
  Timestamp                = {2014.12.09}
}
@inproceedings{muja2012fast,
title={Fast matching of binary features},
author={Muja, Marius and Lowe, David G},
booktitle={Computer and Robot Vision (CRV), 2012 Ninth Conference on},
pages={404--410},
year={2012},
organization={IEEE}
}

@Article{Mullane2011,
  author        = {Mullane, J. and Ba-Ngu Vo and Adams, M.D. and Ba-Tuong Vo},
  title         = {A Random-Finite-Set Approach to Bayesian SLAM},
  journal       = {IEEE Transactions on Robotics},
  year          = {2011},
  volume        = {27},
  number        = {2},
  pages         = {268--282},
  month         = {\#apr\#},
  issn          = {1552-3098},
  __markedentry = {[y:5]},
  comment       = {RFS理论第一次应用到SLAM中，经典作品。},
  file          = {Published version:Mullane2011.pdf:PDF},
  keywords      = {rfs, phd, important, rank5},
  owner         = {y},
  timestamp     = {2014.08.24},
}

@Article{Munguia2013,
  Title                    = {A Robust Approach for a Filter-Based Monocular Simultaneous Localization and Mapping ({SLAM}) System},
  Author                   = {Munguia, R. and Castillo-Toledo, B. and Grau, A.},
  Journal                  = {Sensors},
  Year                     = {2013},
  Number                   = {7},
  Pages                    = {8501--8522},
  Volume                   = {13},

  ISSN                     = {1424-8220},
  Keywords                 = {monocular SLAM mobile robotics stochastic estimation localization mapping real-time 3-d motion vision algorithms navigation features tracking depth},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Mur-Artal2015,
  author    = {Mur-Artal, Raul and Montiel, JMM and Tardos, Juan D},
  title     = {ORB-SLAM: a Versatile and Accurate Monocular SLAM System},
  journal   = {arXiv preprint arXiv:1502.00956},
  year      = {2015},
  comment   = {orb-slam},
  file      = {Mur-Artal2015.pdf:Mur-Artal2015.pdf:PDF},
  keywords  = {rank5},
  owner     = {x},
  timestamp = {2015.08.30},
}

@InProceedings{Newcombe2011,
  Title                    = {KinectFusion: Real-time dense surface mapping and tracking},
  Author                   = {Newcombe, Richard A and Davison, Andrew J and Izadi, Shahram and Kohli, Pushmeet and Hilliges, Otmar and Shotton, Jamie and Molyneaux, David and Hodges, Steve and Kim, David and Fitzgibbon, Andrew},
  Booktitle                = {2011 10th IEEE international symposium on Mixed and augmented reality (ISMAR)},
  Year                     = {2011},
  Organization             = {IEEE},
  Pages                    = {127--136},

  File                     = {Published version:Newcombe2011.pdf:PDF},
  Keywords                 = {kinectfusion, rgb-d SLAM},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Newcombe2015,
  author    = {Newcombe, Richard A and Fox, Dieter and Seitz, Steven M},
  title     = {Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time},
  booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition},
  year      = {2015},
  pages     = {343--352},
}

@Article{Ng2011,
  Title                    = {Sparse autoencoder},
  Author                   = {Ng, Andrew},
  Journal                  = {CS294A Lecture notes},
  Year                     = {2011},
  Volume                   = {72},

  Owner                    = {zero},
  Timestamp                = {2015.04.09}
}

@Article{Nguyen2015,
  Title                    = {Structural Modeling from Depth Images},
  Author                   = {Nguyen, T. and Reitmayr, G. and Schmalstieg, D.},
  Journal                  = {Visualization and Computer Graphics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {Nov},
  Number                   = {11},
  Pages                    = {1230-1240},
  Volume                   = {21},

  Doi                      = {10.1109/TVCG.2015.2459831},
  ISSN                     = {1077-2626},
  Keywords                 = {Cameras;Computational modeling;Feature extraction;Image reconstruction;Simultaneous localization and mapping;Solid modeling;Three-dimensional displays;Structural modeling;geometric scene understanding;topology construction},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Nister2004,
  Title                    = {Visual odometry},
  Author                   = {Nist{\'e}r, David and Naroditsky, Oleg and Bergen, James},
  Booktitle                = {Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on},
  Year                     = {2004},
  Organization             = {IEEE},
  Pages                    = {I--652},
  Volume                   = {1},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@Article{Nister2004a,
  author    = {Nist{\'e}r, David},
  title     = {An efficient solution to the five-point relative pose problem},
  journal   = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year      = {2004},
  volume    = {26},
  number    = {6},
  pages     = {756--770},
  publisher = {IEEE},
}

@InProceedings{Nister2006,
  author       = {Nister, David and Stewenius, Henrik},
  title        = {Scalable recognition with a vocabulary tree},
  booktitle    = {2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)},
  year         = {2006},
  volume       = {2},
  pages        = {2161--2168},
  organization = {IEEE},
  owner        = {cyang},
  timestamp    = {2016.10.02},
}

@Article{Nuechter2007,
  Title                    = {6D SLAM-3D mapping outdoor environments},
  Author                   = {N{\"u}chter, Andreas and Lingemann, Kai and Hertzberg, Joachim and Surmann, Hartmut},
  Journal                  = {Journal of Field Robotics},
  Year                     = {2007},
  Number                   = {8-9},
  Pages                    = {699--722},
  Volume                   = {24},

  Owner                    = {x},
  Publisher                = {Wiley Online Library},
  Timestamp                = {2015.05.18}
}

@Article{Nuechter2008,
  author =         {N{\"u}chter, Andreas and Hertzberg, Joachim},
  title =          {Towards semantic maps for mobile robots},
  journal =        {Robotics and Autonomous Systems},
  year =           {2008},
  volume =         {56},
  number =         {11},
  pages =          {915--926},
  file =           {Published version:Nuechter2008.pdf:PDF},
  keywords =       {qualityAssured, rank3},
  owner =          {GaoXiang},
  publisher =      {Elsevier},
  timestamp =      {2014.03.18}
}

@Article{Nuetzi2011,
  Title                    = {Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM},
  Author                   = {Nuetzi, Gabriel and Weiss, Stephan and Scaramuzza, Davide and Siegwart, Roland},
  Journal                  = {Journal of Intelligent \& Robotic Systems},
  Year                     = {2011},
  Number                   = {1-4SI},
  Pages                    = {287--299},
  Volume                   = {61},

  File                     = {Published version:Nuetzi2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Olson2003,
  Title                    = {Rover navigation using stereo ego-motion},
  Author                   = {Olson, Clark F and Matthies, Larry H and Schoppers, Marcel and Maimone, Mark W},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2003},
  Number                   = {4},
  Pages                    = {215--229},
  Volume                   = {43},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.18}
}

@Article{Olson2007,
  author    = {Olson, Clark F and Matthies, Larry H and Wright, John R and Li, Rongxing and Di, Kaichang},
  title     = {Visual terrain mapping for Mars exploration},
  journal   = {Computer Vision and Image Understanding},
  year      = {2007},
  volume    = {105},
  number    = {1},
  pages     = {73--85},
  comment   = {SLAM在exploration里的应用},
  owner     = {x},
  publisher = {Elsevier},
  timestamp = {2015.05.17},
}

@Article{Olson2013,
  Title                    = {Inference on networks of mixtures for robust robot mapping},
  Author                   = {Olson, Edwin and Agarwal, Pratik},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {7},
  Pages                    = {826--840},
  Volume                   = {32},

  Abstract                 = {The central challenge in robotic mapping is obtaining reliable data associations (or {\textquotedblleft}loop closures{\textquotedblright}): state-of-the-art inference algorithms can fail catastrophically if even one erroneous loop closure is incorporated into the map. Consequently, much work has been done to push error rates closer to zero. However, a long-lived or multi-robot system will still encounter errors, leading to system failure. We propose a fundamentally different approach: allow richer error models that allow the probability of a failure to be explicitly modeled. In other words, rather than characterizing loop closures as being {\textquotedblleft}right{\textquotedblright} or {\textquotedblleft}wrong{\textquotedblright}, we propose characterizing the error of those loop closures in a more expressive manner that can account for their non-Gaussian behavior. Our approach leads to an fully integrated Bayesian framework for dealing with error-prone data. Unlike earlier multiple-hypothesis approaches, our approach avoids exponential memory complexity and is fast enough for real-time performance. We show that the proposed method not only allows loop closing errors to be automatically identified, but also that in extreme cases, the {\textquotedblleft}front-end{\textquotedblright} loop-validation systems can be unnecessary. We demonstrate our system both on standard benchmarks and on the real-world data sets that motivated this work.},
  Eprint                   = {http://ijr.sagepub.com/content/32/7/826.full.pdf+html},
  File                     = {Published version:Olson2013.pdf:PDF},
  Keywords                 = {loop closure,},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Ott2013,
  Title                    = {Unsupervised online learning for long-term autonomy},
  Author                   = {Ott, Lionel and Ramos, Fabio},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1724--1741},
  Volume                   = {32},

  __markedentry            = {[x:]},
  Abstract                 = {A reliable representation of the environment a robot operates in is vital for solving complex tasks. Models that represent information about objects and their properties are typically trained beforehand using supervised methods. This requires intensive human labeling which makes it time-consuming and results in models that are generally inflexible to changes. We would prefer a robot that can build a model of the environment autonomously by learning the different objects and their corresponding properties without human supervision. This would enable the robot to adapt to changes in the environment as well as reduce the effort of deploying a robot to a new environment. In this paper we present solutions to these problems based on novel extensions of affinity propagation; a clustering method that can be executed in real time to produce meaningful models from observations gathered by a robot. Our method is applied to two different tasks. We demonstrate how to automatically learn models for predicting collisions from raw laser data. Then, the method is used to learn visual appearance models of the environment to recognize and avoid obstacles. In both cases, there is no human supervision; the methodology is entirely based on sensory information gathered by the robot and its interaction with the environment. In experiments we show how meta-point affinity propagation performs similarly to standard affinity propagation, while being faster and capable of handling much larger data-sets. Furthermore, we show how different features influence the prediction quality of the model for collision prediction from laser scans. Finally, we show how we successfully build and maintain an appearance model for obstacle detection which can be used to detect obstacles well before a collision could occur.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1724},
  File                     = {Published version:Ott2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@InCollection{Paletta2013,
  author    = {Paletta, Lucas and Santner, Katrin and Fritz, Gerald and Hofmann, Albert and Lodron, Gerald and Thallinger, Georg and Mayer, Heinzena},
  title     = {FACTS-a computer vision system for 3D recovery and semantic mapping of human factors},
  booktitle = {Computer Vision Systems},
  publisher = {Springer},
  year      = {2013},
  pages     = {62--72},
  file      = {Published version:Paletta2013.pdf:PDF},
  owner     = {GaoXiang},
  timestamp = {2014.01.13},
}

@Article{Pathak2010,
  author         = {Pathak, Kaustubh and Birk, Andreas and Vaskevicius, Narunas and Poppinga, Jann},
  title          = {Fast registration based on noisy planes with unknown correspondences for 3-D mapping},
  journal        = {IEEE Transactions on Robotics},
  year           = {2010},
  volume         = {26},
  number         = {3},
  pages          = {424--441},
  __markedentry  = {[y:5]},
  comment        = {以平面为基本特征的SLAM，非常有创意，作品也很完整�?�},
  file           = {Published version:Pathak2010.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {y},
  publisher      = {IEEE},
  timestamp      = {2014.04.29},
}

@Article{Paul2013,
  Title                    = {Self-help: Seeking out perplexing images for ever improving topological mapping},
  Author                   = {Paul, Rohan and Newman, Paul},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1742--1766},
  Volume                   = {32},

  Abstract                 = {In this work, we present a novel approach that allows a robot to improve its own navigation performance through introspection and then targeted data retrieval. It is a step in the direction of life-long learning and adaptation and is motivated by the desire to build robots that have plastic competencies which are not baked in. They should react to and benefit from use. We consider a particular instantiation of this problem in the context of place recognition. Based on a topic-based probabilistic representation for images, we use a measure of perplexity to evaluate how well a working set of background images explain the robot{\textquoteright}s online view of the world. Offline, the robot then searches an external resource to seek out additional background images that bolster its ability to localize in its environment when used next. In this way the robot adapts and improves performance through use. We demonstrate this approach using data collected from a mobile robot operating in outdoor workspaces.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1742},
  File                     = {Paul2013.pdf:Paul2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Paull2014,
  Title                    = {AUV Navigation and Localization: A Review},
  Author                   = {Paull, L. and Saeedi, S. and Seto, M. and Li, H.},
  Journal                  = {Oceanic Engineering, IEEE Journal of},
  Year                     = {2014},

  Month                    = {Jan},
  Number                   = {1},
  Pages                    = {131-149},
  Volume                   = {39},

  Doi                      = {10.1109/JOE.2013.2278891},
  ISSN                     = {0364-9059},
  Keywords                 = {Global Positioning System;SLAM (robots);autonomous underwater vehicles;AUV localization problem;GPS;Global Positioning System;autonomous underwater vehicle;expensive inertial sensors;radio-frequency signals;simultaneous localization and mapping technology;underwater communications;Acoustics;Simultaneous localization and mapping;Sonar navigation;Autonomous underwater vehicles (AUVs);marine navigation;simultaneous localization and mapping},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Paz2008,
  Title                    = {Divide and Conquer: EKF SLAM in O(n)},
  Author                   = {Paz, Lina M and Tard{\'o}s, Juan D and Neira, Jos{\'e}},
  Journal                  = {IEEE Transactions on Robotics},
  Year                     = {2008},
  Number                   = {5},
  Pages                    = {1107--1120},
  Volume                   = {24},

  __markedentry            = {[y:5]},
  File                     = {:Paz2008.pdf:PDF},
  Keywords                 = {EKF, important},
  Owner                    = {y},
  Publisher                = {IEEE},
  Timestamp                = {2014.04.27}
}

@Article{Penate-SanchezAndrade-CettoMoreno-Noguer2013,
  author    = {Penate-Sanchez, Adrian and Andrade-Cetto, Juan and Moreno-Noguer, Francesc},
  title     = {Exhaustive linearization for robust camera pose and focal length estimation},
  journal   = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year      = {2013},
  volume    = {35},
  number    = {10},
  pages     = {2387--2400},
  publisher = {IEEE},
}

@InProceedings{Pinies2006,
  author       = {Pini{\'e}s, Pedro and Tard{\'o}s, Juan D and Neira, Jos{\'e}},
  title        = {Localization of avalanche victims using robocentric SLAM},
  booktitle    = {Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on},
  year         = {2006},
  pages        = {3074--3079},
  organization = {IEEE},
  comment      = {SLAM在救援中的应用},
  owner        = {x},
  timestamp    = {2015.05.17},
}

@Article{Pinies2008,
  Title                    = {Large-scale slam building conditionally independent local maps: Application to monocular vision},
  Author                   = {Pini{\'e}s, Pedro and Tard{\'o}s, Juan D},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2008},
  Number                   = {5},
  Pages                    = {1094--1106},
  Volume                   = {24},

  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.05.18}
}

@InProceedings{Pizzoli2014,
  author       = {Pizzoli, Matia and Forster, Christian and Scaramuzza, Davide},
  title        = {REMODE: Probabilistic, monocular dense reconstruction in real time},
  booktitle    = {2014 IEEE International Conference on Robotics and Automation (ICRA)},
  year         = {2014},
  pages        = {2609--2616},
  organization = {IEEE},
  file         = {Pizzoli2014.pdf:Pizzoli2014.pdf:PDF},
}

@Article{PomerleauColasSiegwart2015,
  author =  {Pomerleau, Fran{\c{c}}ois and Colas, Francis and Siegwart, Roland},
  title =   {A review of point cloud registration algorithms for mobile robotics},
  journal = {Foundations and Trends in Robotics (FnTROB)},
  year =    {2015},
  volume =  {4},
  number =  {1},
  pages =   {1--104}
}

@InProceedings{Poultney2006,
  author    = {Poultney, Christopher and Chopra, Sumit and Cun, Yann L and others},
  title     = {Efficient learning of sparse representations with an energy-based model},
  booktitle = {Advances in neural information processing systems},
  year      = {2006},
  pages     = {1137--1144},
  comment   = {sparse auto-encoder},
  keywords  = {rank1},
  owner     = {x},
  timestamp = {2015.05.02},
}

@Article{Pretto2011,
  Title                    = {Omnidirectional dense large-scale mapping and navigation based on meaningful triangulation},
  Author                   = {Pretto, A. and Menegatti, E. and Pagello, E.},
  Journal                  = {2011 IEEE International Conference on Robotics and Automation (ICRA 2011)},
  Year                     = {2011},
  Pages                    = {3289--96},

  File                     = {Published version:Pretto2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Pronobis2010,
  Title                    = {Representing spatial knowledge in mobile cognitive systems},
  Author                   = {Pronobis, Andrzej and Sj{\"o}{\"o}, Kristoffer and Aydemir, Alper and Bishop, Adrian N and Jensfelt, Patric},
  Booktitle                = {11th International Conference on Intelligent Autonomous Systems (IAS-11), Ottawa, Canada},
  Year                     = {2010},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Puente2014,
  Title                    = {Feature based graph-SLAM in structured environments},
  Author                   = {de la Puente, P. and Rodriguez-Losada, D.},
  Journal                  = {Autonomous Robots},
  Year                     = {2014},
  Number                   = {3},
  Pages                    = {243--260},
  Volume                   = {37},

  File                     = {Puente2014.pdf:Puente2014.pdf:PDF},
  ISSN                     = {0929-5593},
  Keywords                 = {Mobile robots Mapping SLAM Structured environments simultaneous localization information algorithm filters},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@InProceedings{Qiang2014,
  Title                    = {RGB-D sensor based mobile robot SLAM in indoor environment},
  Author                   = {Lyu Qiang and Liu Feng and Wang Xiaolong and Wang Guosheng},
  Booktitle                = {The 26Chinese Control and Decision Conference (2014 CCDC)},
  Year                     = {2014},
  Month                    = {\#may\#},
  Pages                    = {3848--3852},

  File                     = {Published version:Qiang2014.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@InCollection{Rao2012,
  Title                    = {CurveSLAM: An approach for Vision-based Navigation without Point Features},
  Author                   = {Rao, Dushyant and Chung, Soon-Jo and Hutchinson, Seth},
  Year                     = {2012},
  Pages                    = {4198--4204},

  __markedentry            = {[y:3]},
  File                     = {Published version:Rao2012.pdf:PDF},
  Keywords                 = {feature,},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@InProceedings{Ren2012,
  Title                    = {Rgb-(d) scene labeling: Features and algorithms},
  Author                   = {Ren, Xiaofeng and Bo, Liefeng and Fox, Dieter},
  Booktitle                = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
  Year                     = {2012},
  Organization             = {IEEE},
  Pages                    = {2759--2766},

  __markedentry            = {[x:]},
  File                     = {Ren2012.pdf:Ren2012.pdf:PDF},
  Owner                    = {zero},
  Timestamp                = {2015.04.09}
}

@Article{Riazuelo2015a,
  Title                    = {RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach},
  Author                   = {Riazuelo, L. and Tenorth, M. and Di Marco, D. and Salas, M. and Galvez-Lopez, D. and Mosenlechner, L. and Kunze, L. and Beetz, M. and Tardos, J.D. and Montano, L. and Martinez Montiel, J.M.},
  Journal                  = {Automation Science and Engineering, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {April},
  Number                   = {2},
  Pages                    = {432-443},
  Volume                   = {12},

  Doi                      = {10.1109/TASE.2014.2377791},
  ISSN                     = {1545-5955},
  Keywords                 = {SLAM (robots);Web services;cloud computing;control engineering computing;intelligent robots;mobile robots;object recognition;ontologies (artificial intelligence);RoboEarth semantic mapping system;SLAM map;Web services;cloud enabled knowledge-based approach;cloud services;intelligent robot;mobile robot;object locations;object model subdatabase;ontology;scene geometry;semantic reasoning;software as a service;Knowledge based systems;Navigation;Search problems;Semantics;Simultaneous localization and mapping;Visualization;Cloud mapping;knowledge representation;object recognition;semantic mapping;visual SLAM},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Ribas2008,
  Title                    = {Underwater SLAM in man-made structured environments},
  Author                   = {Ribas, David and Ridao, Pere and Tard{\'o}s, Juan Domingo and Neira, Jos{\'e}},
  Journal                  = {Journal of Field Robotics},
  Year                     = {2008},
  Number                   = {11-12},
  Pages                    = {898--921},
  Volume                   = {25},

  Owner                    = {x},
  Publisher                = {Wiley Online Library},
  Timestamp                = {2015.05.18}
}

@Article{Robertson2004,
  author    = {Robertson, Stephen},
  title     = {Understanding inverse document frequency: on theoretical arguments for IDF},
  journal   = {Journal of documentation},
  year      = {2004},
  volume    = {60},
  number    = {5},
  pages     = {503--520},
  owner     = {cyang},
  publisher = {Emerald Group Publishing Limited},
  timestamp = {2016.10.02},
}

@InCollection{Rogers2011,
  Title                    = {Simultaneous Localization and Mapping with Learned Object Recognition and Semantic Data Association},
  Author                   = {Rogers, John G. III and Trevor, Alexander J. B. and Nieto-Granda, Carlos and Christensen, Henrik I.},
  Year                     = {2011},
  Pages                    = {1264--1270},

  File                     = {Published version:Rogers2011.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Rosen2014,
  author    = {Rosen, David M and Kaess, Michael and Leonard, John J},
  title     = {RISE: An incremental trust-region method for robust online sparse least-squares estimation},
  journal   = {IEEE Transactions on Robotics},
  year      = {2014},
  volume    = {30},
  number    = {5},
  pages     = {1091--1108},
  publisher = {IEEE},
}

@Article{Rosin1999,
  author    = {Rosin, Paul L},
  title     = {Measuring corner properties},
  journal   = {Computer Vision and Image Understanding},
  year      = {1999},
  volume    = {73},
  number    = {2},
  pages     = {291--307},
  publisher = {Elsevier},
}

@InCollection{Rosten2006,
  Title                    = {Machine learning for high-speed corner detection},
  Author                   = {Rosten, Edward and Drummond, Tom},
  Booktitle                = {Computer Vision--ECCV 2006},
  Publisher                = {Springer},
  Year                     = {2006},
  Pages                    = {430--443},

  Keywords                 = {FAST},
  Owner                    = {x},
  Timestamp                = {2014.09.30}
}

@Article{Royer2007,
  Title                    = {Monocular Vision for Mobile Robot Localization and Autonomous Navigation},
  Author                   = {Royer, Eric and Lhuillier, Maxime and Dhome, Michel and Lavest, Jean-Marc},
  Journal                  = {International Journal of Computer Vision},
  Year                     = {2007},
  Number                   = {3},
  Pages                    = {237--260},
  Volume                   = {74},

  File                     = {Published version:Royer2007.pdf:PDF},
  ISSN                     = {0920-5691},
  Keywords                 = {localization; navigation; vision; mobile robot; structure from motion},
  Language                 = {English},
  Owner                    = {y},
  Publisher                = {Kluwer Academic Publishers-Plenum Publishers},
  Timestamp                = {2014.08.25}
}

@InProceedings{Rublee2011,
  author       = {Rublee, Ethan and Rabaud, Vincent and Konolige, Kurt and Bradski, Gary},
  title        = {ORB: an efficient alternative to SIFT or SURF},
  booktitle    = {2011 IEEE International Conference on Computer Vision (ICCV)},
  year         = {2011},
  pages        = {2564--2571},
  organization = {IEEE},
  comment      = {ORB},
  owner        = {x},
  timestamp    = {2014.12.11},
}

@InProceedings{Ruhr2012,
  Title                    = {A generalized framework for opening doors and drawers in kitchen environments},
  Author                   = {Ruhr, T and Sturm, J{\"u}rgen and Pangercic, Dejan and Beetz, Michael and Cremers, Daniel},
  Booktitle                = {2012 IEEE International Conference on Robotics and Automation (ICRA)},
  Year                     = {2012},
  Organization             = {IEEE},
  Pages                    = {3852--3858},

  __markedentry            = {[y:1]},
  File                     = {Published version:Ruhr2012.pdf:PDF},
  Keywords                 = {high-level feature,rgb-d SLAM},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@PhdThesis{Rusu2009,
  author    = {Radu Bogdan Rusu},
  title     = {Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments},
  school    = {Computer Science department, Technische Universitaet Muenchen, Germany},
  year      = {2009},
  month     = {October},
  comment   = {FPFH等很多点云特征的提出者�?�},
  owner     = {x},
  timestamp = {2014.12.04},
}

@InProceedings{Rusu2011,
  author       = {Rusu, Radu Bogdan and Cousins, Steve},
  title        = {3d is here: Point cloud library (PCL)},
  booktitle    = {Robotics and Automation (ICRA), 2011 IEEE International Conference on},
  year         = {2011},
  pages        = {1--4},
  organization = {IEEE},
  comment      = {PCL},
  owner        = {x},
  timestamp    = {2014.12.10},
}

@Article{Saarinen2013,
  Title                    = {3D normal distributions transform occupancy maps: An efficient representation for mapping in dynamic environments},
  Author                   = {Saarinen, Jari P. and Andreasson, Henrik and Stoyanov, Todor and Lilienthal, Achim J.},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1627--1644},
  Volume                   = {32},

  __markedentry            = {[y:3]},
  Abstract                 = {In order to enable long-term operation of autonomous vehicles in industrial environments numerous challenges need to be addressed. A basic requirement for many applications is the creation and maintenance of consistent 3D world models. This article proposes a novel 3D spatial representation for online real-world mapping, building upon two known representations: normal distributions transform (NDT) maps and occupancy grid maps. The proposed normal distributions transform occupancy map (NDT-OM) combines the advantages of both representations; compactness of NDT maps and robustness of occupancy maps. One key contribution in this article is that we formulate an exact recursive updates for NDT-OMs. We show that the recursive update equations provide natural support for multi-resolution maps. Next, we describe a modification of the recursive update equations that allows adaptation in dynamic environments. As a second key contribution we introduce NDT-OMs and formulate the occupancy update equations that allow to build consistent maps in dynamic environments. The update of the occupancy values are based on an efficient probabilistic sensor model that is specially formulated for NDT-OMs. In several experiments with a total of 17 hours of data from a milk factory we demonstrate that NDT-OMs enable real-time performance in large-scale, long-term industrial setups.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1627},
  File                     = {Published version:Saarinen2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Saeedi2011,
  author         = {Saeedi, S. and Paull, L. and Trentini, M. and Li, H.},
  title          = {Neural Network-Based Multiple Robot Simultaneous Localization and Mapping},
  journal        = {IEEE Transactions on Neural Networks},
  year           = {2011},
  volume         = {22},
  number         = {12},
  pages          = {2376--2387},
  issn           = {1045-9227},
  comment        = {14.10.28 主题是Map fusion，讲如何把两个不同位置的机器人生成的地图拼合起来。机器人之间没有meeting. 特点是用到了神经网络，先从grid地图中提取特征，然后计算两个地图之间的旋转与平移。},
  file           = {Saeedi2011.pdf:Saeedi2011.pdf:PDF},
  keywords       = {Map fusion Radon transform self-organizing map simultaneous localization and mapping (SLAM) self-organizing maps slam filters, rank2, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Saeedi2014,
  author =    {Saeedi, S. and Paull, L. and Trentini, M. and Seto, M. and Li, H.},
  title =     {Map merging for multiple robots using Hough peak matching},
  journal =   {Robotics and Autonomous Systems},
  year =      {2014},
  volume =    {62},
  number =    {10},
  pages =     {1408--1424},
  file =      {Saeedi2014.pdf:Saeedi2014.pdf:PDF},
  issn =      {0921-8890},
  keywords =  {Simultaneous localization and mapping (SLAM) Multiple robot Map merging Hough space and image entropy particle filters mobile robots localization, rank2},
  owner =     {x},
  timestamp = {2014.10.19},
  type =      {Journal Article}
}

@Article{Salas-Moreno2013,
  author         = {Salas-Moreno, R. F. and Newcombe, R. A. and Strasdat, H. and Kelly, P. H. J. and Davison, A. J.},
  title          = {SLAM++: Simultaneous Localisation and Mapping at the Level of Objects},
  journal        = {2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year           = {2013},
  pages          = {1352--9},
  __markedentry  = {[y:3]},
  comment        = {SLAM++ 名字取的非常好听，�?�且说是基于物体的SLAM�???????????? 无奈用了太多GPU上的东西，不太看的明白�?��?�且没有那么好的GPU，么破�?�},
  file           = {Published version:Salas-Moreno2013.pdf:PDF},
  keywords       = {kinectfusion, qualityAssured, rank3},
  owner          = {GaoXiang},
  timestamp      = {2014.01.13},
}

@Article{Sarkar2014,
  author         = {Sarkar, B. and Pal, P. K. and Sarkar, D.},
  title          = {Building maps of indoor environments by merging line segments extracted from registered laser range scans},
  journal        = {Robotics and Autonomous Systems},
  year           = {2014},
  volume         = {62},
  number         = {4},
  pages          = {603--615},
  issn           = {0921-8890},
  comment        = {14.10.27 中规中矩的一篇小文章。Range sensor. 线段地图�??? 亮点：对地图进行线聚类（算法没细看，直观上想象起来觉得不复杂），提取其中的线段，去掉其中较短的，以线段来表达地图 优点：占用空间少，具有较好的缩放性（scale well with the map size），浮点精确�??? 缺点：离线算法，不�?�合动�?�场合�?�},
  file           = {Sarkar2014.pdf:Sarkar2014.pdf:PDF},
  keywords       = {Clustering Ground truth Laser range data Line merging Line segment Map building Map assessment mean shift simultaneous localization clustering-algorithm hausdorff distance mobile robotics recognition navigation images slam, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@Article{Scaramuzza2008,
  Title                    = {Appearance-guided monocular omnidirectional visual odometry for outdoor ground vehicles},
  Author                   = {Scaramuzza, Davide and Siegwart, Roland},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2008},
  Number                   = {5},
  Pages                    = {1015--1026},
  Volume                   = {24},

  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.05.18}
}

@Article{Scaramuzza2011,
  Title                    = {Visual Odometry [Tutorial]},
  Author                   = {D. Scaramuzza and F. Fraundorfer},
  Journal                  = {IEEE Robotics Automation Magazine},
  Year                     = {2011},

  Month                    = {Dec},
  Number                   = {4},
  Pages                    = {80-92},
  Volume                   = {18},

  Doi                      = {10.1109/MRA.2011.943233},
  File                     = {Scaramuzza2011.pdf:pdf\\Scaramuzza2011.pdf:PDF},
  ISSN                     = {1070-9932},
  Keywords                 = {cameras;image texture;motion estimation;pose estimation;road vehicles;robots;wheels;augmented reality;automotive;egomotion estimation;illumination;image texture;multiple cameras;onboard cameras;pose estimation;robotics;scene overlap;single camera;vehicle;visual odometry;wearable computing;wheel odometry;wheels},
  Owner                    = {x},
  Timestamp                = {2016.05.29}
}

@Article{Schwendner2014,
  Title                    = {Using Embodied Data for Localization and Mapping},
  Author                   = {Schwendner, Jakob and Joyeux, Sylvain and Kirchner, Frank},
  Journal                  = {Journal of Field Robotics},
  Year                     = {2014},
  Number                   = {2},
  Pages                    = {263--295},
  Volume                   = {31},

  Abstract                 = {Mobile autonomous robots have finally emerged from the confined spaces of structured and controlled indoor environments. To fulfill the promises of ubiquitous robotics in unstructured outdoor environments, robust navigation is a key requirement. The research in the simultaneous localization and mapping (SLAM) community has largely focused on optical sensors to solve this problem, and the fact that the robot is a physical entity has largely been ignored. In this paper, a hierarchical SLAM framework is proposed that takes the interaction of the robot with the environment into account. A sequential Monte Carlo filter is used to generate local map segments with a combination of visual and embodied data associations. Constraints between segments are used to generate globally consistent maps with a focus on suitability for navigation tasks. The proposed method is experimentally verified on two different outdoor robots. The results show that the approach is viable and that the rich modeling of the robot with its environment provides a new modality with the potential for improving existing visual methods and extending the availability of SLAM in domains where visual processing alone is not sufficient.},
  ISSN                     = {1556-4967},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@Article{Se2002,
  Title                    = {Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks},
  Author                   = {Se, Stephen and Lowe, David and Little, Jim},
  Journal                  = {The international Journal of robotics Research},
  Year                     = {2002},
  Number                   = {8},
  Pages                    = {735--758},
  Volume                   = {21},

  File                     = {Published version:Se2002.pdf:PDF},
  Keywords                 = {classic, feature, SIFT},
  Owner                    = {y},
  Publisher                = {SAGE Publications},
  Timestamp                = {2014.08.24}
}

@Article{Se2005,
  author    = {Se, Stephen and Lowe, David G and Little, James J},
  title     = {Vision-based global localization and mapping for mobile robots},
  journal   = {Robotics, IEEE Transactions on},
  year      = {2005},
  volume    = {21},
  number    = {3},
  pages     = {364--375},
  comment   = {待读 visual SLAM出处},
  owner     = {x},
  publisher = {IEEE},
  timestamp = {2015.05.17},
}

@Article{Shao2012,
  Title                    = {An Interactive Approach to Semantic Modeling of Indoor Scenes with an RGBD Camera},
  Author                   = {Shao, Tianjia and Xu, Weiwei and Zhou, Kun and Wang, Jingdong and Li, Dongping and Guo, Baining},
  Journal                  = {ACM Trans. Graph.},
  Year                     = {2012},

  Month                    = nov,
  Number                   = {6},
  Pages                    = {136:1--136:11},
  Volume                   = {31},

  Acmid                    = {2366155},
  Address                  = {New York, NY, USA},
  Articleno                = {136},
  File                     = {Shao2012.pdf:Shao2012.pdf:PDF},
  ISSN                     = {0730-0301},
  Issue_date               = {November 2012},
  Keywords                 = {depth images, indoor scene, labeling, random regress forest, segmentation},
  Numpages                 = {11},
  Owner                    = {x},
  Publisher                = {ACM},
  Timestamp                = {2015.06.01}
}

@Article{Sheng2015,
  author         = {Sheng, Weihua and Du, Jianhao and Cheng, Qi and Li, Gang and Zhu, Chun and Liu, Meiqin and Xu, Guoqing},
  title          = {Robot semantic mapping through human activity recognition: A wearable sensing and computing approach},
  journal        = {Robotics and Autonomous Systems},
  year           = {2015},
  volume         = {68},
  pages          = {47--58},
  comment        = {15.5.19 可穿戴设�?+SLAM=语义地图 可穿戴设备能识别人的动作，例如坐�?、躺�?等等，SLAM使用了现成的算法。原理简单，不需要图像识别，但很实用。结果能够识别出小场景里的各个物体，并与人的行为相关联：躺在床上，在书架边读书�?? 缺点是家具识别是静�?�的，需要事先假设环境里有哪些家具�?�},
  file           = {Sheng2015.pdf:Sheng2015.pdf:PDF},
  keywords       = {qualityAssured, rank3},
  owner          = {x},
  publisher      = {Elsevier},
  timestamp      = {2015.05.19},
}

@InProceedings{Shi1994,
  author         = {Shi, Jianbo and Tomasi, Carlo},
  title          = {Good features to track},
  booktitle      = {Computer Vision and Pattern Recognition, 1994. Proceedings CVPR'94., 1994 IEEE Computer Society Conference on},
  year           = {1994},
  pages          = {593--600},
  organization   = {IEEE},
  comment        = {GFTT特征的开篇文章�?�},
  keywords       = {GFTT, feature, qualityAssured, rank1},
  owner          = {x},
  timestamp      = {2014.09.30},
}

@Article{Shi2013,
  author        = {Shi, Zongying and Liu, Zhibin and Wu, Xianliang and Xu, Wenli},
  title         = {Feature selection for reliable data association in visual SLAM},
  journal       = {Machine Vision and Applications},
  year          = {2013},
  volume        = {24},
  number        = {4},
  pages         = {667--682},
  issn          = {0932-8092},
  __markedentry = {[y:4]},
  comment       = {居然是徐文立的学生，我原先�?�么不知道！ 用了�????????????种原创的方法进行特征选择和评估，主要应用于monocular SLAM中�?�},
  file          = {Published version:Shi2013.pdf:PDF},
  keywords      = {feature},
  language      = {English},
  owner         = {y},
  publisher     = {Springer-Verlag},
  timestamp     = {2014.08.25},
}

@InProceedings{Shin2010,
  Title                    = {Unsupervised discovery of repetitive objects},
  Author                   = {Shin, Jiwon and Triebel, Rudolph and Siegwart, Roland},
  Booktitle                = {Robotics and Automation (ICRA), 2010 IEEE International Conference on},
  Year                     = {2010},
  Organization             = {IEEE},
  Pages                    = {5041--5046},

  Owner                    = {x},
  Timestamp                = {2015.05.22}
}

@Article{Siagian2014,
  author         = {Siagian, C. and Chang, C. K. and Itti, L.},
  title          = {Autonomous Mobile Robot Localization and Navigation Using a Hierarchical Map Representation Primarily Guided by Vision},
  journal        = {Journal of Field Robotics},
  year           = {2014},
  volume         = {31},
  number         = {3},
  pages          = {408--440},
  issn           = {1556-4959},
  comment        = {14.10.20 文章实在太猛。三十页�???????????? 野外，实战，完整，不过对机器人的要求很高，很复杂�???????????? 贡献有好几处：视觉定位�?�道路检测，自动驾驶�???????????? 不过，由于是野外场景，光�????????????/动�?�情形与室内有明显差别，做的东西也不完全相关�???????????? 可作为引�????????????参�?�文献�?�},
  file           = {Siagian2014.pdf:Siagian2014.pdf:PDF},
  keywords       = {spatial semantic hierarchy inspired slam system collision-avoidance obstacle avoidance visual-attention probabilistic localization outdoor environments scene classification monocular vision features, rank4, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Sibley2009,
  author         = {Sibley, Dieter and Mei, Christopher and Reid, Ian and Newman, Paul},
  title          = {Adaptive relative bundle adjustment},
  booktitle      = {Robotics: science and systems},
  year           = {2009},
  comment        = {BA经典文章。必引�?�},
  file           = {Published version:Sibley2009.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {y},
  timestamp      = {2014.08.24},
}

@Article{Sibley2009a,
  author         = {Sibley, Gabe},
  title          = {Relative bundle adjustment},
  journal        = {Department of Engineering Science, Oxford University, Tech. Rep},
  year           = {2009},
  volume         = {2307},
  number         = {09},
  comment        = {BA另一篇经典文章�?�},
  file           = {Published version:Sibley2009a.pdf:PDF},
  keywords       = {qualityAssured, rank5},
  owner          = {y},
  timestamp      = {2014.04.27},
}

@Article{Siddiqui2013,
  author         = {Siddiqui, J.Rafid and Havaei, Mohammad and Khatibi, Siamak and Lindley, CraigA.},
  title          = {A novel plane extraction approach using supervised learning},
  journal        = {Machine Vision and Applications},
  year           = {2013},
  volume         = {24},
  number         = {6},
  pages          = {1229--1237},
  issn           = {0932-8092},
  __markedentry  = {[y:2]},
  comment        = {提平面的方法�???????????? 用非监督学习来弄，似乎有点小题大做了�???????????? 但是也可以试试�?�},
  file           = {Published version:Siddiqui2013.pdf:PDF},
  keywords       = {planar feature, qualityAssured, rank3},
  language       = {English},
  owner          = {y},
  publisher      = {Springer Berlin Heidelberg},
  timestamp      = {2014.08.25},
}

@InCollection{Silberman2012,
  author         = {Silberman, Nathan and Hoiem, Derek and Kohli, Pushmeet and Fergus, Rob},
  title          = {Indoor segmentation and support inference from RGBD images},
  booktitle      = {Computer Vision--ECCV 2012},
  publisher      = {Springer},
  year           = {2012},
  pages          = {746--760},
  __markedentry  = {[x:]},
  comment        = {Gupta2014: 早期的Bottum-up Segmentation的代表作； NYUD2数据集的提供者；},
  keywords       = {qualityAssured},
  owner          = {x},
  timestamp      = {2015.05.24},
}

@Article{Silveira2008,
  author         = {Silveira, G. and Malis, E. and Rives, Patrick},
  title          = {An Efficient Direct Approach to Visual SLAM},
  journal        = {IEEE Transactions on Robotics},
  year           = {2008},
  volume         = {24},
  number         = {5},
  pages          = {969--979},
  issn           = {1552-3098},
  comment        = {direct方法做SLAM，不提特征�?? 虽然很独特，但是个人觉得没什么前途�?�现在特征对于SLAM各个方面影响都很大�?�},
  doi            = {10.1109/TRO.2008.2004829},
  file           = {Published version:Silveira2008.pdf:PDF},
  keywords       = {direct slam, qualityAssured, rank4},
  owner          = {y},
  timestamp      = {2014.08.24},
  url            = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4633681},
}

@Article{Sim2007,
  author    = {Sim, Robert and Elinas, Pantelis and Little, JamesJ.},
  title     = {A Study of the Rao-Blackwellised Particle Filter for Efficient and Accurate Vision-Based SLAM},
  journal   = {International Journal of Computer Vision},
  year      = {2007},
  volume    = {74},
  number    = {3},
  pages     = {303--318},
  issn      = {0920-5691},
  comment   = {RBPF SLAM�????????????山之作�?? 还没看，有时间一定要看�?�},
  file      = {Published version:Sim2007.pdf:PDF},
  keywords  = {rank5},
  language  = {English},
  owner     = {y},
  publisher = {Kluwer Academic Publishers-Plenum Publishers},
  timestamp = {2014.08.24},
}

@InProceedings{Sivic2003,
  author       = {Sivic, Josef and Zisserman, Andrew},
  title        = {Video Google: A text retrieval approach to object matching in videos},
  booktitle    = {Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on},
  year         = {2003},
  pages        = {1470--1477},
  organization = {IEEE},
  owner        = {cyang},
  timestamp    = {2016.10.02},
}

@Article{Smith1986,
  author         = {Smith, Randall C. and Cheeseman, Peter},
  title          = {On the Representation and Estimation of Spatial Uncertainty},
  journal        = {International Journal of Robotics Research},
  year           = {1986},
  volume         = {5},
  number         = {4},
  pages          = {56--68},
  __markedentry  = {[x:]},
  abstract       = {This paper describes a general method for estimating the nominal relationship and expected error (covariance) between coordinate frames representing the relative locations of ob jects. The frames may be known only indirectly through a series of spatial relationships, each with its associated error, arising from diverse causes, including positioning errors, measurement errors, or tolerances in part dimensions. This estimation method can be used to answer such questions as whether a camera attached to a robot is likely to have a particular reference object in its field of view. The calculated estimates agree well with those from an independent Monte Carlo simulation. The method makes it possible to decide in advance whether an uncertain relationship is known accu rately enough for some task and, if not, how much of an improvement in locational knowledge a proposed sensor will provide. The method presented can be generalized to six degrees offreedom and provides a practical means of esti mating the relationships ( position and orientation) among objects, as well as estimating the uncertainty associated with the relationships.},
  comment        = {SLAM 领域的开篇之作，很经典，EKF实现。},
  file           = {Published version:Smith1986.pdf:PDF},
  keywords       = {first, SLAM, qualityAssured, rank5},
  owner          = {x},
  timestamp      = {2014.10.05},
}

@InCollection{Smith1990,
  author =         {Smith, Randall and Self, Matthew and Cheeseman, Peter},
  title =          {Estimating uncertain spatial relationships in robotics},
  booktitle =      {Autonomous robot vehicles},
  publisher =      {Springer},
  year =           {1990},
  pages =          {167--193},
  __markedentry =  {[y:5]},
  file =           {Published version:Smith1990.pdf:PDF},
  keywords =       {EKF, classical, first, qualityAssured, rank5},
  owner =          {y},
  timestamp =      {2014.08.24}
}

@Misc{Sola2016,
  author = {Sola, Joan},
  title  = {Course on SLAM},
  year   = {2016},
  howpublished = {\url{https://github.com/joansola/slamtb/raw/graph/courseSLAM.pdf}}
}

@Article{Spica2014,
  Title                    = {Active Structure From Motion: Application to Point, Sphere, and Cylinder},
  Author                   = {Spica, R. and Giordano, P.R. and Chaumette, F.},
  Journal                  = {Robotics, IEEE Transactions on},
  Year                     = {2014},

  Month                    = {Dec},
  Number                   = {6},
  Pages                    = {1499-1513},
  Volume                   = {30},

  Doi                      = {10.1109/TRO.2014.2365652},
  File                     = {Spica2014.pdf:Spica2014.pdf:PDF},
  ISSN                     = {1552-3098},
  Keywords                 = {Convergence;Estimation error;Image processing;Transient response;Visual servoing;Nonlinear estimation;structure from motion;visual servoing},
  Owner                    = {x},
  Timestamp                = {2015.01.01}
}

@Article{Steder2008,
  author    = {Steder, Bastian and Grisetti, Giorgio and Stachniss, Cyrill and Burgard, Wolfram},
  title     = {Visual SLAM for flying vehicles},
  journal   = {Robotics, IEEE Transactions on},
  year      = {2008},
  volume    = {24},
  number    = {5},
  pages     = {1088--1093},
  comment   = {SLAM在空中机器人的应用},
  owner     = {x},
  publisher = {IEEE},
  timestamp = {2015.05.17},
}

@Misc{stereo-matching-website,
  title        = {Correlation based similarity measure-Summary},
  howpublished = {\url{https://siddhantahuja.wordpress.com/tag/stereo-matching/}},
}

@Article{Strasdat2011,
  author    = {Strasdat, Hauke and Davison, Andrew J. and Montiel, J. M. M. and Konolige, Kurt},
  title     = {Double Window Optimisation for Constant Time Visual {SLAM}},
  journal   = {2011 IEEE International Conference On Computer Vision (ICCV)},
  year      = {2011},
  pages     = {2352--2359},
  file      = {Published version:Strasdat2011.pdf:PDF},
  owner     = {GaoXiang},
  timestamp = {2014.01.13},
}

@Article{Strasdat2012,
  author         = {Strasdat, Hauke and Montiel, Jos{\'e} MM and Davison, Andrew J},
  title          = {Visual slam: Why filter?},
  journal        = {Image and Vision Computing},
  year           = {2012},
  volume         = {30},
  number         = {2},
  pages          = {65--77},
  __markedentry  = {[y:5]},
  comment        = {why filter? 事实证明后来filter还是有起色的。},
  file           = {Published version:Strasdat2012.pdf:PDF},
  keywords       = {graph-based slam, survey, important, qualityAssured, rank4},
  owner          = {y},
  publisher      = {Elsevier},
  timestamp      = {2014.04.27},
}

@PhdThesis{Strasdat2012a,
  author = {Strasdat, Hauke},
  title =  {Local accuracy and global consistency for efficient visual slam},
  school = {Citeseer},
  year =   {2012}
}

@Article{Stuckler2014,
  author         = {Stuckler, J. and Behnke, S.},
  title          = {Multi-resolution surfel maps for efficient dense 3D modeling and tracking},
  journal        = {Journal of Visual Communication and Image Representation},
  year           = {2014},
  volume         = {25},
  number         = {1},
  pages          = {137--147},
  issn           = {1047-3203},
  comment        = {14.10.20 工作内容和我上一篇文章十分相似�?�亮点在于Surfel的引入，使用的范围包括定位与建图�??? Surfel是一种八叉树的结构，可表示多分辨率的地图，亦可提取位置特征进行跟踪与配准�??? 优点：地图比较漂亮�?? drawback: 数据集挑的偏�???单了。源代码：http://code.google.com/p/mrsmap},
  file           = {Stuckler2014.pdf:Stuckler2014.pdf:PDF},
  keywords       = {3D multi-resolution RGB-D image representation Real-time RGB-D image registration Visual odometry Dense object modeling Dense indoor scene mapping Real-time simultaneous localization and mapping On-line loop-closure detection Real-time pose tracking scan registration, rank4, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Stueckler2012,
  author         = {St{\"u}ckler, J{\"o}rg and Biresev, Nenad and Behnke, Sven},
  title          = {Semantic mapping using object-class segmentation of RGB-D images},
  booktitle      = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year           = {2012},
  pages          = {3005--3010},
  organization   = {IEEE},
}

@InProceedings{Stuehmer2010,
  author       = {St{\"u}hmer, Jan and Gumhold, Stefan and Cremers, Daniel},
  title        = {Real-time dense geometry from a handheld camera},
  booktitle    = {Joint Pattern Recognition Symposium},
  year         = {2010},
  pages        = {11--20},
  organization = {Springer},
}

@Article{Stuelpnagel1964,
  author    = {Stuelpnagel, John},
  title     = {On the parametrization of the three-dimensional rotation group},
  journal   = {SIAM Review},
  year      = {1964},
  volume    = {6},
  number    = {4},
  pages     = {422--430},
  publisher = {SIAM},
}

@InProceedings{Sturm2012,
  author         = {Sturm, J{\"u}rgen and Engelhard, Nikolas and Endres, Felix and Burgard, Wolfram and Cremers, Daniel},
  title          = {A benchmark for the evaluation of RGB-D {SLAM} systems},
  booktitle      = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year           = {2012},
  pages          = {573--580},
  organization   = {IEEE},
  __markedentry  = {[y:4]},
  comment        = {数据集，没什么好说吧�???????????? 凡是用到该数据集的都得引它�?�},
  file           = {Published version:Sturm2012.pdf:PDF},
  keywords       = {benchmark, rgb-d SLAM, qualityAssured, rank5},
  owner          = {GaoXiang},
  timestamp      = {2014.04.19},
}

@InProceedings{Su2013,
  author =         {Po-Chang Su and Ju Shen and Cheung, S.-C.S.},
  title =          {A robust RGB-D SLAM system for 3D environment with planar surfaces},
  booktitle =      {Image Processing (ICIP), 2013 20th IEEE International Conference on},
  year =           {2013},
  pages =          {275-279},
  month =          {Sept},
  file =           {Su2013.pdf:Su2013.pdf:PDF},
  keywords =       {SLAM (robots), cameras, feature extraction, image colour analysis, image reconstruction, image registration, iterative methods, robot vision, 3D environment, 3D space, ICP algorithm, Microsoft Kinect sensor, RGB-depth sensor, back-projects, captured 3D point cloud registration, color information, depth information, depth variations, feature extraction, indoor environment reconstruction, iterative closest point algorithm, movable RGB-D sensor, planar surfaces, point correspondence, rigid camera movement, robust RGB-D SLAM system, scanning large planar regions, simultaneous location and mapping system, wall surfaces, Cameras, Image color analysis, Image reconstruction, Iterative closest point algorithm, Simultaneous localization and mapping, Surface reconstruction, Three-dimensional displays, 3D Reconstruction, Iterative Closest Point (ICP), Large-scale planar surface alignment, Ray casting TSDF, Truncated Signed Distance Function, qualityAssured, rank1},
  owner =          {x},
  timestamp =      {2014.12.08}
}

@Article{Sujan2005,
  author                     = {Sujan, VA and Dubowsky, S},
  title                      = {Efficient information-based visual robotic mapping in unstructured environments},
  journal                    = {International Journal of Robotics Research},
  year                       = {2005},
  volume                     = {24},
  number                     = {4},
  pages                      = {275--293},
  abstract                   = {Infield environments it is often not possible to provide robot teams with detailed a priori environment and task models. In such unstructured environments, robots will need to create a dimensionally accurate three-dimensional geometric model of its surroundings by performing appropriate sensor actions. However, uncertainties in robot locations and sensing limitations/occlusions make this difficult. A new algorithm, based on iterative sensor planning and sensor redundancy, is proposed to build a geometrically consistent dimensional map of the environment for mobile robots that have articulated sensors. The aim is to acquire new information that leads to more detailed and complete knowledge of the environment. The robot(s) is controlled to maximize geometric knowledge gained of its environment using an evaluation function based on Shannon's information theory. Using the measured and Markovian predictions of the unknown environment, an information theory based metric is maximized to determine a robotic agent's next best view (NBV) of the environment. Data collected at this NB V pose are fused using a Kalman filter statistical uncertainty model to the measured environment map. The process continues until the environment mapping process is complete. The work is unique in the application of information theory to enhance the performance of environment sensing robot agents. It may be used by multiple distributed and decentralized sensing agents for efficient and accurate cooperative environment modeling. The algorithm makes no assumptions of the environment structure. Hence, it is robust to robot failure since the environment model being built is not dependent on any single agent frame, but is set in an absolute reference frame. It accounts for sensing uncertainty, robot motion uncertainty, environment model uncertainty and other critical parameters. It allows for regions of higher interest receiving greater attention by the agents. This algorithm is particularly well suited to unstructured environments, where sensor uncertainty and occlusions are significant. Simulations and experiments show the effectiveness of this algorithm.},
  address                    = {{1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}},
  affiliation                = {{Sujan, VA (Reprint Author), MIT, Dept Mech Engn, Cambridge, MA 02139 USA. MIT, Dept Mech Engn, Cambridge, MA 02139 USA.}},
  author-email               = {{vasujan@mit.edu}},
  doc-delivery-number        = {{917MX}},
  issn                       = {{0278-3649}},
  journal-iso                = {{Int. J. Robot. Res.}},
  keywords                   = {application, planetary},
  keywords-plus              = {{SIMULTANEOUS LOCALIZATION; NAVIGATION}},
  language                   = {{English}},
  number-of-cited-references = {{35}},
  owner                      = {x},
  publisher                  = {{SAGE PUBLICATIONS LTD}},
  research-areas             = {{Robotics}},
  times-cited                = {{28}},
  timestamp                  = {2014.10.05},
  type                       = {{Article}},
  unique-id                  = {{ISI:000228467600003}},
  web-of-science-categories  = {{Robotics}},
}

@Article{Sun2011,
  author         = {Sun, R. C. and Ma, S. G. and Li, B. and Wang, M. H. and Wang, Y. C.},
  title          = {A Simultaneous Localization and Mapping Algorithm in Complex Environments: SLASEM},
  journal        = {Advanced Robotics},
  year           = {2011},
  volume         = {25},
  number         = {6-7},
  pages          = {941--962},
  issn           = {0169-1864},
  comment        = {14.10.24 未细看�?�用Sampled environment map (SEM)对环境进行建2D模型，与gampping结果进行了对比�?�SEM具体是什么东西还不太清楚。沈阳自动化研究院做的�?�东西挺不错。},
  file           = {Sun2011.pdf:Sun2011.pdf:PDF},
  keywords       = {Localization mapping SLAM Kalman filter mobile robots planar curves slam problem segmentation surfaces filters, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Sun2013,
  Title                    = {Attribute based object identification},
  Author                   = {Sun, Yuyin and Bo, Liefeng and Fox, Dieter},
  Booktitle                = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {2096--2103},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Sundaram2012,
  Title                    = {What Are We Doing Here? Egocentric Activity Recognition on the Move for Contextual Mapping},
  Author                   = {Sundaram, Sudeep and Mayol-Cuevas, Walterio W.},
  Journal                  = {2012 IEEE International Conference On Robotics And Automation (ICRA)},
  Year                     = {2012},
  Pages                    = {877--882},

  File                     = {Published version:Sundaram2012.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13},
  Url                      = {http://www.cs.bris.ac.uk/Publications/Papers/2001491.pdf}
}

@Article{Taguchi2013,
  author         = {Taguchi, Y. and Yong-Dian, Jian and Ramalingam, S. and Chen, Feng},
  title          = {Point-Plane SLAM for Hand-Held 3D Sensors},
  journal        = {IEEE International Conference on Robotics and Automation (ICRA)},
  year           = {2013},
  pages          = {5182--9},
  __markedentry  = {[y:5]},
  comment        = {将平面与点结合起来一起用的SLAM。挺有新意�?�},
  file           = {Published version:Taguchi2013.pdf:PDF},
  keywords       = {qualityAssured, rank4},
  owner          = {GaoXiang},
  timestamp      = {2014.04.19},
}

@InBook{Takeda2012,
  Title                    = {Study on the Indoor SLAM Using Kinect},
  Author                   = {Takeda, Yoshiaki and Aoyama, Norifumi and Tanaami, Takahiro and Mizumi, Syoto and Kamata, Hiroyuki},
  Editor                   = {Kim, J. H. and Lee, K. and Tanaka, S. and Park, S. H.},
  Pages                    = {217--225},
  Year                     = {2012},
  Series                   = {Proceedings in Information and Communications Technology},
  Type                     = {Book Section},
  Volume                   = {4},

  Booktitle                = {Advanced Methods, Techniques, and Applications in Modeling and Simulation},
  ISBN                     = {1867-2914 978-4-431-54216-2},
  Owner                    = {x},
  Timestamp                = {2014.10.19}
}

@Article{Tanaka2012,
  Title                    = {Dictionary-Based Map Compression for Sparse Feature Maps},
  Author                   = {Tanaka, K. and Nagasaka, T.},
  Journal                  = {Ieice Transactions on Information and Systems},
  Year                     = {2012},
  Number                   = {2},
  Pages                    = {604--613},
  Volume                   = {E95D},

  Doi                      = {10.1587/transinf.E95.D.604},
  File                     = {Tanaka2012.pdf:Tanaka2012.pdf:PDF;Tanaka2012.pdf:Tanaka2012.pdf:PDF},
  ISSN                     = {0916-8532},
  Keywords                 = {mobile robots map compression dictionary-based compression sparse coding only slam},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article},
  Url                      = {<Go to ISI>://WOS:000300471900037}
}

@Article{Tardos2002,
  Title                    = {Robust mapping and localization in indoor environments using sonar data},
  Author                   = {Tard{\'o}s, Juan D and Neira, Jos{\'e} and Newman, Paul M and Leonard, John J},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2002},
  Number                   = {4},
  Pages                    = {311--330},
  Volume                   = {21},

  Owner                    = {zero},
  Publisher                = {SAGE Publications},
  Timestamp                = {2015.05.18}
}

@InProceedings{Teo2013,
  Title                    = {Embedding high-level information into low level vision: Efficient object search in clutter},
  Author                   = {Teo, Ching Lik and Myers, Austin and Fermuller, Cornelia and Aloimonos, Yiannis},
  Booktitle                = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {126--132},

  Owner                    = {x},
  Timestamp                = {2015.05.24}
}

@Article{Teslic2011,
  Title                    = {EKF-based localization of a wheeled mobile robot in structured environments},
  Author                   = {Tesli{\'c}, Luka and {\v{S}}krjanc, Igor and Klan{\v{c}}ar, Gregor},
  Journal                  = {Journal of Intelligent \& Robotic Systems},
  Year                     = {2011},
  Number                   = {2},
  Pages                    = {187--203},
  Volume                   = {62},

  Keywords                 = {LRF},
  Owner                    = {x},
  Publisher                = {Springer},
  Timestamp                = {2014.09.30}
}

@InProceedings{Thrun2003,
  author       = {Thrun, Sebastian and Hahnel, Dirk and Ferguson, David and Montemerlo, D and Triebel, Rudolph and Burgard, Wolfram and Baker, Christopher and Omohundro, Zachary and Thayer, Scott and Whittaker, William},
  title        = {A system for volumetric robotic mapping of abandoned mines},
  booktitle    = {Robotics and Automation, 2003. Proceedings. ICRA'03. IEEE International Conference on},
  year         = {2003},
  volume       = {3},
  pages        = {4270--4275},
  organization = {IEEE},
  comment      = {SLAM在矿井救援里的应用},
  owner        = {x},
  timestamp    = {2015.05.17},
}

@Book{Thrun2005,
  Title                    = {Probabilistic robotics},
  Author                   = {Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter},
  Publisher                = {MIT Press},
  Year                     = {2005},

  Owner                    = {x},
  Timestamp                = {2016.06.18}
}

@Article{Thrun2006,
  Title                    = {The graph slam algorithm with applications to large-scale mapping of urban structures},
  Author                   = {Thrun, Sebastian and Montemerlo, Michael},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2006},
  Number                   = {5-6},
  Pages                    = {403--429},
  Volume                   = {25},

  Abstract                 = { This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lower-dimensional problems that is then solved using conventional optimization techniques. As a result, GraphSLAM can generate maps with 108 or more features. The paper discusses a greedy algorithm for data association, and presents results for SLAM in urban environments with occasional GPS measurements. },
  File                     = {Published version:Thrun2006.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2014.10.11}
}

@InProceedings{Tian2013,
  Title                    = {RGB-D based cognitive map building and navigation},
  Author                   = {Tian, Bo and Shim, Vui Ann and Yuan, Miaolong and Srinivasan, Chellam and Tang, Huajin and Li, Haizhou},
  Booktitle                = {Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on},
  Year                     = {2013},
  Organization             = {IEEE},
  Pages                    = {1562--1567},

  Owner                    = {x},
  Timestamp                = {2015.09.09}
}

@Article{Tipaldi2013,
  Title                    = {Lifelong localization in changing environments},
  Author                   = {Tipaldi, Gian Diego and Meyer-Delius, Daniel and Burgard, Wolfram},
  Journal                  = {The International Journal of Robotics Research},
  Year                     = {2013},
  Number                   = {14},
  Pages                    = {1662--1678},
  Volume                   = {32},

  Abstract                 = {Robot localization systems typically assume that the environment is static, ignoring the dynamics inherent in most real-world settings. Corresponding scenarios include households, offices, warehouses and parking lots, where the location of certain objects such as goods, furniture or cars can change over time. These changes typically lead to inconsistent observations with respect to previously learned maps and thus decrease the localization accuracy or even prevent the robot from globally localizing itself. In this paper we present a sound probabilistic approach to lifelong localization in changing environments using a combination of a Rao-Blackwellized particle filter with a hidden Markov model. By exploiting several properties of this model, we obtain a highly efficient map management approach for dynamic environments, which makes it feasible to run our algorithm online. Extensive experiments with a real robot in a dynamically changing environment demonstrate that our algorithm reliably adapts to changes in the environment and also outperforms the popular Monte-Carlo localization approach.},
  Eprint                   = {http://ijr.sagepub.com/cgi/reprint/32/14/1662},
  File                     = {Published version:Tipaldi2013.pdf:PDF},
  Owner                    = {y},
  Timestamp                = {2014.08.24}
}

@Article{Tomatis2003,
  Title                    = {Hybrid simultaneous localization and map building: a natural integration of topological and metric},
  Author                   = {Tomatis, N and Nourbakhsh, I and Siegwart, R},
  Journal                  = {Robotics And Autonomous Systems},
  Year                     = {2003},

  Month                    = {\#jul\#},
  Note                     = {4th European Workshop on Advanced Mobile robots (EUROBOT 2001), LUND, SWEDEN, SEP, 2001},
  Number                   = {1},
  Pages                    = {3--14},
  Volume                   = {44},

  Abstract                 = {{In this paper the metric and topological paradigms are integrated in a hybrid system for both localization and map building. A global topological map connects local metric maps, allowing a compact environment model, which does not require global metric consistency and permits both precision and robustness. Furthermore, the approach handles loops in the environment during automatic mapping by means of the information of the multimodal topological localization. The system uses a 360degrees laser scanner to extract corners and openings for the topological approach and lines for the metric method. This hybrid approach has been tested in a 50 m x 25 m portion of the institute building with the fully autonomous robot Donald Duck. Experiments are of four types: maps created by a complete exploration of the environment are compared to estimate their quality; test missions are randomly generated in order to evaluate the efficiency of the approach for both the localization and relocation; the fourth type of experiments shows the practicability of the approach for closing the loop. (C) 2003 Elsevier Science B.V. All rights reserved.}},
  ISSN                     = {{0921-8890}},
  Orcid-numbers            = {{Siegwart, Roland/0000-0002-2760-7983}},
  Owner                    = {x},
  Researcherid-numbers     = {{Siegwart, Roland/A-4495-2008}},
  Timestamp                = {2014.10.05},
  Unique-id                = {{ISI:000184108100002}}
}

@InProceedings{Trevor2012,
  author =         {Trevor, A.J.B. and Rogers, J.G. and Christensen, H.I.},
  title =          {Planar surface SLAM with 3D and 2D sensors},
  booktitle =      {2012 IEEE International Conference on Robotics and Automation (ICRA)},
  year =           {2012},
  pages =          {3041-3048},
  month =          {May},
  file =           {Trevor2012.pdf:Trevor2012.pdf:PDF},
  issn =           {1050-4729},
  keywords =       {SLAM (robots), sensors, service robots, 2D laser scans, 2D sensors, 3D point clouds, 3D sensors, SLAM, feature based mapping technique, planar surface, service robots, Feature extraction, Measurement by laser beam, Simultaneous localization and mapping, Trajectory, qualityAssured, rank1},
  owner =          {x},
  timestamp =      {2014.12.08}
}

@InCollection{Triggs2000,
  author         = {Triggs, Bill and McLauchlan, Philip F and Hartley, Richard I and Fitzgibbon, Andrew W},
  title          = {Bundle adjustment: a modern synthesis},
  booktitle      = {Vision algorithms: theory and practice},
  publisher      = {Springer},
  year           = {2000},
  pages          = {298--372},
  __markedentry  = {[y:5]},
  file           = {Published version:Triggs2000.pdf:PDF},
  keywords       = {BA, important, qualityAssured, rank5},
  owner          = {y},
  timestamp      = {2014.04.27},
}

@Article{Troiani2014,
  Title                    = {Low computational-complexity algorithms for vision-aided inertial navigation of micro aerial vehicles},
  Author                   = {Troiani, Chiara and Martinelli, Agostino and Laugier, Christian and Scaramuzza, Davide},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2014},

  File                     = {Troiani2014.pdf:Troiani2014.pdf:PDF},
  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.19}
}

@Article{Tully2012,
  Title                    = {A unified Bayesian framework for global localization and SLAM in hybrid metric/topological maps},
  Author                   = {Tully, S. and Kantor, G. and Choset, H.},
  Journal                  = {International Journal of Robotics Research},
  Year                     = {2012},
  Number                   = {3},
  Pages                    = {271--288},
  Volume                   = {31},

  ISSN                     = {0278-3649},
  Keywords                 = {Topology SLAM localization Bayesian filtering mapping topological slam mobile robots model},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Ulas2013,
  author         = {Ulas, C. and Temeltas, H.},
  title          = {3D Multi-Layered Normal Distribution Transform for Fast and Long Range Scan Matching},
  journal        = {Journal of Intelligent \& Robotic Systems},
  year           = {2013},
  volume         = {71},
  number         = {1},
  pages          = {85--108},
  issn           = {0921-0296},
  note           = {Times Cited: 0 Ulas, Cihan Temeltas, Hakan 0},
  comment        = {14.10.29 ICP：点对点，点对平面�?? NDT：将点云分成若干个cell，拟合小平面，计算法线的分布�???????????? NDT中，cell大小的�?�择至关重要，因此作者给出了�????????????个层级网络�?�},
  file           = {Ulas2013.pdf:Ulas2013.pdf:PDF},
  keywords       = {3D scan matching Normal distribution transform SLAM registration, rank3, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Ulrich2000,
  Title                    = {Appearance-based place recognition for topological localization},
  Author                   = {Ulrich, Iwan and Nourbakhsh, Illah},
  Booktitle                = {Robotics and Automation, 2000. Proceedings. ICRA'00. IEEE International Conference on},
  Year                     = {2000},
  Organization             = {Ieee},
  Pages                    = {1023--1029},
  Volume                   = {2},

  Owner                    = {zero},
  Timestamp                = {2015.04.22}
}

@Article{Valencia2013,
  Title                    = {Planning reliable paths with Pose SLAM},
  Author                   = {Valencia, Rafael and Morta, Mart{\i} and Andrade-Cetto, Juan and Porta, Josep M},
  Journal                  = {IEEE Transactions on Robotics},
  Year                     = {2013},

  Month                    = {\#aug\#},
  Pages                    = {1050--1059},
  Volume                   = {29},

  File                     = {Published version:Valencia2013.pdf:PDF},
  Owner                    = {GaoXiang},
  Publisher                = {IEEE},
  Timestamp                = {2014.04.30}
}

@Article{Vazquez-Martin2013,
  Title                    = {Spatio-temporal feature-based keyframe detection from video shots using spectral clustering},
  Author                   = {Vazquez-Martin, R. and Bandera, A.},
  Journal                  = {Pattern Recognition Letters},
  Year                     = {2013},
  Number                   = {7},
  Pages                    = {770--779},
  Volume                   = {34},

  ISSN                     = {0167-8655},
  Keywords                 = {keyframe detection Spectral clustering Similarity measure slam},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Ventura2014,
  Title                    = {Global Localization from Monocular SLAM on a Mobile Phone},
  Author                   = {Ventura, J. and Arth, C. and Reitmayr, G. and Schmalstieg, D.},
  Journal                  = {Visualization and Computer Graphics, IEEE Transactions on},
  Year                     = {2014},

  Month                    = {April},
  Number                   = {4},
  Pages                    = {531-539},
  Volume                   = {20},

  Doi                      = {10.1109/TVCG.2014.27},
  ISSN                     = {1077-2626},
  Keywords                 = {SLAM (robots);image sensors;pose estimation;smart phones;6DoF pose estimation;SLAM map registration;SLAM system;camera locations;field-of-view mobile phone camera;global localization method;keyframe images;mobile client;mobile device;monocular SLAM;server process;Cameras;Feature extraction;Global Positioning System;Mobile handsets;Real-time systems;Servers;Simultaneous localization and mapping;Image-based localization; monocular SLAM; real-time tracking; global positioning; mobile augmented reality},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@Article{Vianchada2014,
  Title                    = {Attitude Estimation using Fusion of Monocular SLAM and Inertial Sensors},
  Author                   = {Vianchada, C. and Escamilla, P.J. and Ibarra, M.N. and Ramirez, J.M. and Gomez, P.},
  Journal                  = {Latin America Transactions, IEEE (Revista IEEE America Latina)},
  Year                     = {2014},

  Month                    = {Sept},
  Number                   = {6},
  Pages                    = {977-984},
  Volume                   = {12},

  Doi                      = {10.1109/TLA.2014.6893989},
  ISSN                     = {1548-0992},
  Keywords                 = {Kalman filters;SLAM (robots);inertial systems;nonlinear filters;sensor fusion;sequential estimation;AHRS;attitude and heading reference system;attitude estimation;extended Kalman filter;inertial sensors;minimum quadratic mean estimator;monocular SLAM fusion;observation vector;orientation measurement;sensor fusion methods;sequential estimator;simultaneous localization and mapping;Estimation;Kalman filters;Media;Sensor fusion;Simultaneous localization and mapping;Vectors;Euler angles;Kalman filter;SLAM;attitude;navigation;quaternions;sensors fusion;simultaneous localization and mapping},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Vidal-Calleja2007,
  Title                    = {On the observability of bearing-only SLAM},
  Author                   = {Vidal-Calleja, Teresa and Bryson, Mitch and Sukkarieh, Salah and Sanfeliu, Alberto and Andrade-Cetto, Juan},
  Booktitle                = {Robotics and Automation, 2007 IEEE International Conference on},
  Year                     = {2007},
  Organization             = {IEEE},
  Pages                    = {4114--4119},

  Owner                    = {x},
  Timestamp                = {2015.05.18}
}

@Article{Vidal-Calleja2011,
  author         = {Vidal-Calleja, T. A. and Berger, C. and Sola, J. and Lacroix, S.},
  title          = {Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain},
  journal        = {Robotics and Autonomous Systems},
  year           = {2011},
  volume         = {59},
  number         = {9},
  pages          = {654--674},
  issn           = {0921-8890},
  comment        = {14.10.27 只看了摘要�?? 多个机器人（实验中用了一个空中和�????????????个地上的）的SLAM。关键问题是在于多个传感器之间的位姿匹配�???????????? 写的还是比较详尽的�?�但是和目前地图表达的问题不直接相关，等研究多机器人协作的时候再考虑这个问题。},
  file           = {Vidal-Calleja2011.pdf:Vidal-Calleja2011.pdf:PDF},
  keywords       = {Multi-robots cooperation Visual SLAM multirobot simultaneous localization slam algorithm representation filters, rank1, qualityAssured},
  owner          = {x},
  timestamp      = {2014.10.19},
  type           = {Journal Article},
}

@InProceedings{Vincent2008,
  Title                    = {Extracting and composing robust features with denoising autoencoders},
  Author                   = {Vincent, Pascal and Larochelle, Hugo and Bengio, Yoshua and Manzagol, Pierre-Antoine},
  Booktitle                = {Proceedings of the 25th international conference on Machine learning},
  Year                     = {2008},
  Organization             = {ACM},
  Pages                    = {1096--1103},

  Owner                    = {zero},
  Timestamp                = {2015.04.09}
}

@Article{Vincent2010,
  author    = {Vincent, Pascal and Larochelle, Hugo and Lajoie, Isabelle and Bengio, Yoshua and Manzagol, Pierre-Antoine},
  title     = {Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion},
  journal   = {The Journal of Machine Learning Research},
  year      = {2010},
  volume    = {11},
  pages     = {3371--3408},
  comment   = {autoencoder},
  owner     = {x},
  publisher = {JMLR. org},
  timestamp = {2015.01.04},
}

@Article{Vogiatzis2011,
  author    = {Vogiatzis, George and Hern{\'a}ndez, Carlos},
  title     = {Video-based, real-time multi-view stereo},
  journal   = {Image and Vision Computing},
  year      = {2011},
  volume    = {29},
  number    = {7},
  pages     = {434--441},
  publisher = {Elsevier},
}

@Article{Wang2008,
  Title                    = {Online mapping with a mobile robot in dynamic and unknown environments},
  Author                   = {H.M. Wang and Z-G. Hou and L. Cheng and M. Tan},
  Journal                  = {International Journal of Modelling, Identification and Control},
  Year                     = {2008},
  Number                   = {4},
  Pages                    = {415-423},
  Volume                   = {4},

  Abstract                 = {In this paper, we address the problem of mapping dynamic and unknown environments. The static and moving objects are modelled as the components in a Gaussian mixture model (GMM). By recursive learning of GMM, the components corresponding to the static objects will have larger weights while the components corresponding to the moving objects will have smaller weights. At each time step, a number of components with the largest weights are adaptively selected as the background map and the new observations which do not match with the background map are classified as the foreground map. In addition, based on a Bayesian factorisation of simultaneous localisation and mapping (SLAM) problem, we present an online algorithm for SLAM with GMM learning. Our contributions are employing GMM learning approach to model the dynamic environment with detection of moving objects and jointing the GMM learning with SLAM in unknown environment. Consequently, an online approach for mapping with a mobile robot in dynamic and unknown environments is presented. Some simulation results indicate that our approach is feasible.},
  Eprint                   = { http://www.inderscienceonline.com/doi/pdf/10.1504/IJMIC.2008.021481 },
  Owner                    = {x},
  Timestamp                = {2015.05.20},
  Url                      = { http://www.inderscienceonline.com/doi/abs/10.1504/IJMIC.2008.021481 
}
}

@Article{Wang2010,
  Title                    = {Visual SLAM and Moving-object Detection for a Small-size Humanoid Robot},
  Author                   = {Wang, Y. T. and Lin, M. C. and Ju, R. C.},
  Journal                  = {International Journal of Advanced Robotic Systems},
  Year                     = {2010},
  Number                   = {2},
  Pages                    = {133--138},
  Volume                   = {7},

  ISSN                     = {1729-8806},
  Keywords                 = {Simultaneous Localization and Mapping (SLAM) Humanoid Robot Moving Object Detection simultaneous localization features},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@Article{Wang2013,
  Title                    = {The nonlinearity structure of point feature SLAM problems with spherical covariance matrices},
  Author                   = {Heng Wang and Shoudong Huang and Udo Frese and Gamini Dissanayake},
  Journal                  = {Automatica },
  Year                     = {2013},
  Number                   = {10},
  Pages                    = {3112--3119},
  Volume                   = {49},

  Abstract                 = {Abstract This paper proves that the optimization problem of one-step point feature Simultaneous Localization and Mapping (SLAM) is equivalent to a nonlinear optimization problem of a single variable when the associated uncertainties can be described using spherical covariance matrices. Furthermore, it is proven that this optimization problem has at most two minima. The necessary and sufficient conditions for the existence of one or two minima are derived in a form that can be easily evaluated using observation and odometry data. It is demonstrated that more than one minimum exists only when the observation and odometry data are extremely inconsistent with each other. A numerical algorithm based on bisection is proposed for solving the one-dimensional nonlinear optimization problem. It is shown that the approach extends to joining of two maps, thus can be used to obtain an approximate solution to the complete \{SLAM\} problem through map joining. },
  File                     = {Published version:Wang2013.pdf:PDF},
  ISSN                     = {0005-1098},
  Owner                    = {y},
  Timestamp                = {2014.08.25}
}

@InProceedings{Wang2013a,
  Title                    = {Learning a deep compact image representation for visual tracking},
  Author                   = {Wang, Naiyan and Yeung, Dit-Yan},
  Booktitle                = {Advances in Neural Information Processing Systems},
  Year                     = {2013},
  Pages                    = {809--817},

  Owner                    = {x},
  Timestamp                = {2015.09.13}
}

@Article{Wang2014,
  author         = {Wang,Yin-Tien and Lin,Guan-Yu},
  title          = {Improvement of speeded-up robust features for robot visual simultaneous localization and mapping},
  journal        = {Robotica},
  year           = {2014},
  volume         = {32},
  pages          = {533--549},
  issn           = {1469-8668},
  __markedentry  = {[y:2]},
  abstract       = {ABSTRACT SUMMARY A robot mapping procedure using a modified speeded-up robust feature (SURF) is proposed for building persistent maps with visual landmarks in robot simultaneous localization and mapping (SLAM). SURFs are scale-invariant features that automatically recover the scale and orientation of image features in different scenes. However, the SURF method is not originally designed for applications in dynamic environments. The repeatability of the detected SURFs will be reduced owing to the dynamic effect. This study investigated and modified SURF algorithms to improve robustness in representing visual landmarks in robot SLAM systems. Many modifications of the SURF algorithms are proposed in this study including the orientation representation of features, the vector dimension of feature description, and the number of detected features in an image. The concept of sparse representation is also used to describe the environmental map and to reduce the computational complexity when using extended Kalman filter (EKF) for state estimation. Effective procedures of data association and map management for SURFs in SLAM are also designed to improve accuracy in robot state estimation. Experimental works were performed on an actual system with binocular vision sensors to validate the feasibility and effectiveness of the proposed algorithms. The experimental examples include the evaluation of state estimation using EKF SLAM and the implementation of indoor SLAM. In the experiments, the performance of the modified SURF algorithms was compared with the original SURF algorithms. The experimental results confirm that the modified SURF provides better repeatability and better robustness for representing the landmarks in visual SLAM systems.},
  comment        = {改进了一下SURF特征},
  file           = {Published version:Wang2014.pdf:PDF},
  issue          = {04},
  keywords       = {feature, vision slam, rank2, qualityAssured},
  numpages       = {17},
  owner          = {y},
  timestamp      = {2014.08.25},
}
 
 @Misc{web:p3p,
 author = "iplimage",
 title = "P3P(Blog)",
 year = "2016",
 howpublished = {\url{"http://iplimage.com/blog/p3p-perspective-point-overview/"}},
 }

@Article{Whelan2015,
  author  = {Whelan, Thomas and Leutenegger, Stefan and Salas-Moreno, Renato F and Glocker, Ben and Davison, Andrew J},
  title   = {ElasticFusion: Dense SLAM without a pose graph},
  journal = {Proc. Robotics: Science and Systems, Rome, Italy},
  year    = {2015},
}

@Misc{wiki:featurecv,
   author = "Wikipedia",
   title = "Feature (computer vision)",
   year = "2016",
   howpublished = {\url{"https://en.wikipedia.org/wiki/Feature_(computer_vision)"}},
   note = "[Online; accessed 09-July-2016]"
 }

@Misc{git-tutor,
	title        = {Git tutor},
	howpublished = {\url{http://www.liaoxuefeng.com/wiki/0013739516305929606dd18361248578c67b8067c8c017b000/}},
	author = "Liao Xuefeng"
}

@Article{Williams2009,
  Title                    = {A comparison of loop closing techniques in monocular SLAM},
  Author                   = {Williams, Brian and Cummins, Mark and Neira, Jos{\'e} and Newman, Paul and Reid, Ian and Tard{\'o}s, Juan},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2009},
  Number                   = {12},
  Pages                    = {1188--1197},
  Volume                   = {57},

  Owner                    = {x},
  Publisher                = {Elsevier},
  Timestamp                = {2015.05.18}
}

@Article{Williams2011,
  author    = {Williams, Brian and Klein, Georg and Reid, Ian},
  title     = {Automatic Relocalization and Loop Closing for Real-Time Monocular {SLAM}},
  journal   = {IEEE Transactions On Pattern Analysis And Machine Intelligence},
  year      = {2011},
  volume    = {33},
  number    = {9},
  pages     = {1699--1712},
  comment   = {SLAM基于Davison的MonoSLAM。主动跟踪角点�?? 本文提出训练方法（分类器），为每�???个触点特征训练一个类别标签，这样新的图像到来时可以知道哪些特征点属于哪个类�?? 分类器使用了决策森林。每�???个节点只是比较两个像素的大小。训练过程用了Wrapping，即把新得的块进行缩放�?�旋转变换后，作为同�???类的样本。},
  file      = {Published version:Williams2011.pdf:PDF},
  owner     = {GaoXiang},
  timestamp = {2014.01.13},
}

@Article{Wu2011,
  Title                    = {An approach to robot SLAM based on incremental appearance learning with omnidirectional vision},
  Author                   = {Wu, H. and Qin, S. Y.},
  Journal                  = {International Journal of Systems Science},
  Year                     = {2011},
  Number                   = {3},
  Pages                    = {407--427},
  Volume                   = {42},

  ISSN                     = {0020-7721},
  Keywords                 = {landmark appearance learning probabilistic PCA incremental SVD omnidirectional vision SLAM simultaneous localization visual odometry features vehicles},
  Owner                    = {x},
  Timestamp                = {2014.10.19},
  Type                     = {Journal Article}
}

@InProceedings{Wu2014,
  Title                    = {Hierarchical semantic labeling for task-relevant rgb-d perception},
  Author                   = {Wu, Chenxia and Lenz, Ian and Saxena, Ashutosh},
  Booktitle                = {Robotics: Science and Systems (RSS)},
  Year                     = {2014},

  File                     = {Wu2014.pdf:Wu2014.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2015.06.01}
}

@InProceedings{Wurm2010,
  Title                    = {OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems},
  Author                   = {Wurm, Kai M and Hornung, Armin and Bennewitz, Maren and Stachniss, Cyrill and Burgard, Wolfram},
  Booktitle                = {Proc. of the ICRA 2010 workshop on best practice in 3D perception and modeling for mobile manipulation},
  Year                     = {2010},
  Volume                   = {2},

  Owner                    = {x},
  Timestamp                = {2015.08.13}
}

@Article{Yang2014,
  Title                    = {Graph-Based Segmentation for RGB-D Data Using 3-D Geometry Enhanced Superpixels},
  Author                   = {Yang, Jingyu and Gan, Ziqiao and Li, Kun and Hou, Chunping},
  Journal                  = {IEEE Transactions on Cybernetics},
  Year                     = {2014},

  __markedentry            = {[x:]},
  File                     = {Yang2014.pdf:Yang2014.pdf:PDF},
  Owner                    = {x},
  Publisher                = {IEEE},
  Timestamp                = {2015.05.26}
}

@Article{Yangming2013,
  Title                    = {A biologically inspired solution to simultaneous localization and consistent mapping in dynamic environments},
  Author                   = {Yangming, Li and Shuai, Li and Yunjian, Ge},
  Journal                  = {Neurocomputing},
  Year                     = {2013},
  Pages                    = {170--9},
  Volume                   = {104},

  __markedentry            = {[y:1]},
  File                     = {Published version:Yangming2013.pdf:PDF},
  Keywords                 = {dynamic, neural network},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@PhdThesis{Ye2013,
  author         = {Ye, Edmund Shanming and Malik, Jitendra},
  title          = {Object detection in rgb-d indoor scenes},
  school         = {EECS Department, University of California, Berkeley},
  year           = {2013},
  comment        = {讲RGB-D图像中的物体识别，使用DPM模型。对节点使用法线进行聚类，成为小平面，然后对这些小平面提取HOG特征。},
  file           = {Ye2013.pdf:Ye2013.pdf:PDF},
  keywords       = {qualityAssured, rank3},
  owner          = {x},
  timestamp      = {2015.05.30},
}

@Article{Ye2015,
  Title                    = {6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features},
  Author                   = {Ye, C. and Hong, S. and Tamjidi, A.},
  Journal                  = {Automation Science and Engineering, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {Oct},
  Number                   = {4},
  Pages                    = {1169-1180},
  Volume                   = {12},

  Doi                      = {10.1109/TASE.2015.2469726},
  ISSN                     = {1545-5955},
  Keywords                 = {Feature extraction;Kalman filters;Navigation;Simultaneous localization and mapping;Visualization;Egomotion estimation;extended Kalman filter (EKF);filter consistency;indoor localization;pose estimation;robotic navigation aid (RNA);simultaneous localization and mapping (SLAM);wayfinding},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Zeiler2011,
  Title                    = {Adaptive deconvolutional networks for mid and high level feature learning},
  Author                   = {Zeiler, Matthew D and Taylor, Graham W and Fergus, Rob},
  Booktitle                = {2011 IEEE International Conference on Computer Vision (ICCV)},
  Year                     = {2011},
  Organization             = {IEEE},
  Pages                    = {2018--2025},

  File                     = {Zeiler2011.pdf:Zeiler2011.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2014.11.16}
}

@Article{Zhang1996,
  author    = {Zhang, Zhongfei and Hanson, Allen R},
  title     = {3D reconstruction based on homography mapping},
  journal   = {ARPA Image Understanding Workshop},
  year      = {1996},
  pages     = {1007--1012},
  publisher = {Citeseer},
}

@Article{Zhang2015,
  Title                    = {Autonomous Flight Control of a Nano Quadrotor Helicopter in a GPS-Denied Environment Using On-Board Vision},
  Author                   = {Xu Zhang and Bin Xian and Bo Zhao and Yao Zhang},
  Journal                  = {Industrial Electronics, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {Oct},
  Number                   = {10},
  Pages                    = {6392-6403},
  Volume                   = {62},

  Doi                      = {10.1109/TIE.2015.2420036},
  ISSN                     = {0278-0046},
  Keywords                 = {SLAM (robots);aircraft control;autonomous aerial vehicles;height measurement;helicopters;microrobots;pose estimation;robot vision;GPS-denied indoor environments;GPS-denied outdoor environments;IMU;SLAM algorithm;attitude data;autonomous flight control development;helicopter translational position estimation;helicopter translational velocity estimation;microinertial measurement unit;microonboard vision system;modified visual simultaneous localization and mapping algorithm;nanoquadrotor helicopter;nonlinear flight controller design;payload ability;quadrotor helicopter;trajectory tracking ability;visual measurement;visual pose measurement;Attitude control;Estimation;Helicopters;Heuristic algorithms;Robot sensing systems;Robustness;Visualization;Nano Quadrotor;Nano quadrotor;Robust Control;UAV;Visual Control;robust control;visual control},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Zhao2014,
  author         = {Zhao, Zhe and Chen, Xiaoping},
  title          = {Semantic mapping for object category and structural class},
  booktitle      = {Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on},
  year           = {2014},
  pages          = {724--729},
  organization   = {IEEE},
  comment        = {这个，没有人吐槽和Cadena那篇太像了么？从方法、数据到结果都十分的相似啊. -CRF是常用的模型，没有说谁用了别人就不能用。这个工作可以看成cadena的后续（尽管实际上是silberman的扩展），因为他把类别结果拓展到了点云，并且类别也更多一些。 我们赶紧来做这件事吧。},
  file           = {Zhao2014.pdf:Zhao2014.pdf:PDF},
  keywords       = {qualityAssured, rank1},
  owner          = {x},
  timestamp      = {2015.05.19},
}

@InProceedings{Zheng2015,
  author =         {Shuai Zheng and Sadeep Jayasumana and Bernardino Romera-Paredes and Vibhav Vineet and Zhizhong Su and Dalong Du and Chang Huang and Philip Torr},
  title =          {Conditional Random Fields as Recurrent Neural Networks},
  booktitle =      {International Conference on Computer Vision (ICCV)},
  year =           {2015},
  file =           {Zheng2015.pdf:Zheng2015.pdf:PDF},
  keywords =       {qualityAssured, rank5},
  owner =          {x},
  timestamp =      {2015.11.09}
}

@Article{Zhou2015,
  Title                    = {StructSLAM: Visual SLAM With Building Structure Lines},
  Author                   = {Huizhong Zhou and Danping Zou and Ling Pei and Rendong Ying and Peilin Liu and Wenxian Yu},
  Journal                  = {Vehicular Technology, IEEE Transactions on},
  Year                     = {2015},

  Month                    = {April},
  Number                   = {4},
  Pages                    = {1364-1375},
  Volume                   = {64},

  Doi                      = {10.1109/TVT.2015.2388780},
  File                     = {Zhou2015.pdf:Zhou2015.pdf:PDF},
  ISSN                     = {0018-9545},
  Keywords                 = {Kalman filters;SLAM (robots);building management systems;image sensors;nonlinear filters;robot vision;structural engineering;DoF;StructSLAM;accumulated orientation errors;building structure lines;camera;computer vision;degree-of-freedom;dominant directions;extended Kalman filter visual SLAM method;global orientation information;loop closing algorithm;man-made building environments;odometer;position drift;public RAWSEEDS data sets;robotics communities;simultaneous localization and mapping method;structural regularity;structure lines;visual SLAM;Buildings;Cameras;Image segmentation;Simultaneous localization and mapping;Three-dimensional displays;Vectors;Visualization;Indoor Scenes;Indoor scenes;Line Features;Manhattan-World Assumption;Manhattan-world assumption;Visual SLAM;line features;visual simultaneous localization and mapping (SLAM)},
  Owner                    = {x},
  Timestamp                = {2015.10.16}
}

@InProceedings{Zhu2014,
  Title                    = {A novel deep model for image recognition},
  Author                   = {Zhu, Ming and Wu, Yan},
  Booktitle                = {Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on},
  Year                     = {2014},
  Organization             = {IEEE},
  Pages                    = {373--376},

  File                     = {Zhu2014.pdf:Zhu2014.pdf:PDF},
  Owner                    = {x},
  Timestamp                = {2014.12.17}
}

@Article{Zi2010,
  Title                    = {Vision-based recognition for robot localization},
  Author                   = {Zi, Xingjian},
  Journal                  = {2010 International Conference on Computer Design and Applications (ICCDA 2010)},
  Year                     = {2010},
  Number                   = {vol.1},
  Pages                    = {422--4},

  File                     = {Published version:Zi2010.pdf:PDF},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Article{Zitova2003,
  Title                    = {Image registration methods: a survey},
  Author                   = {Barbara Zitov{\'{a}} and Jan Flusser},
  Journal                  = {Image and Vision Computing },
  Year                     = {2003},
  Number                   = {11},
  Pages                    = {977--1000},
  Volume                   = {21},

  Abstract                 = {This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align two images (the reference and sensed images). The reviewed approaches are classified according to their nature (area-based and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping function design, and image transformation and resampling. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of image registration and outlook for the future research are discussed too. The major goal of the paper is to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas. },
  File                     = {Published version:Zitova2003.pdf:PDF},
  ISSN                     = {0262-8856},
  Keywords                 = {Image registration},
  Owner                    = {x},
  Timestamp                = {2014.09.28}
}

@Article{Zou2013,
  Title                    = {CoSLAM: Collaborative Visual {SLAM} in Dynamic Environments},
  Author                   = {Zou, Danping and Tan, Ping},
  Journal                  = {IEEE Transactions On Pattern Analysis And Machine Intelligence},
  Year                     = {2013},
  Number                   = {2},
  Pages                    = {354--366},
  Volume                   = {35},

  File                     = {Published version:Zou2013.pdf:PDF},
  Keywords                 = {dynamic, collabrative slam, important},
  Owner                    = {GaoXiang},
  Timestamp                = {2014.01.13}
}

@Book{文俊2003数学机械化,
  title =     {数学机械化},
  publisher = {科学出版社},
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  author =    {文俊}
}

@Article{Liang2013,
  author  = {Mingjie Liang and Huaqing Min and Ronghua Luo},
  title   = {Graph-based SLAM: A Survey},
  journal = {ROBOT},
  year    = {2013},
  volume  = {35},
  number  = {4},
  pages   = {500-512},
  note    = {in Chinese},
}

@Article{Rueckauer2016,
  author    = {Rueckauer, Bodo and Delbruck, Tobi},
  title     = {Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor},
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  year      = {2016},
  volume    = {10},
  publisher = {Frontiers Media SA},
}

@inproceedings{agarwal2010bundle,
  title={Bundle adjustment in the large},
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  pages={29--42},
  year={2010},
  organization={Springer}
}

@inproceedings{carlone2014mining,
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  author={Carlone, Luca and Alcantarilla, Pablo Fernandez and Chiu, Han-Pang and Kira, Zsolt and Dellaert, Frank},
  booktitle={Proceedings of British Machine Vision Conference (BMVC)},
  year={2014}
}


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@inproceedings{agarwal2012variable,
  title={Variable reordering strategies for SLAM},
  author={Agarwal, Pratik and Olson, Edwin},
  booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  pages={3844--3850},
  year={2012},
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@Article{chen2008algorithm,
  author    = {Chen, Yanqing and Davis, Timothy A and Hager, William W and Rajamanickam, SivasankaranSLAM},
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@Misc{Davis2005,
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  year   = {2005},
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  title={Bundle Adjustment in the Large},
 
  howpublished={\url{http://grail.cs.washington.edu/projects/bal/}}

}

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@Misc{Ceres,
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  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year      = {2016},
  month     = {May},
  file      = {Usenko2016.pdf:Usenko2016.pdf:PDF},
  keywords  = {visual inertial odometry, sensor fusion},
  owner     = {cyang},
  timestamp = {2016.09.26},
}

@Misc{wiki:RANSAC,
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@InProceedings{Li2010,
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@Article{Janabi-Sharifi2010,
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@InProceedings{Polok2013,
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  year      = {2013},
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@Article{Gao2015b,
  author    = {Gao, Xiang and Zhang, Tao},
  title     = {Unsupervised learning to detect loops using deep neural networks for visual SLAM system},
  journal   = {Autonomous Robots},
  year      = {2015},
  pages     = {1--18},
  owner     = {cyang},
  publisher = {Springer},
  timestamp = {2016.09.28},
}

@Article{Gui2015,
  author      = {Gui, Jianjun and Gu, Dongbing and Wang, Sen and Hu, Huosheng},
  title       = {A review of visual inertial odometry from filtering and optimisation perspectives},
  journal     = {Advanced Robotics},
  year        = {{2015}},
  volume      = {{29}},
  number      = {{20}},
  pages       = {{1289-1301}},
  month       = {{Oct 18}},
  doi         = {{10.1080/01691864.2015.1057616}},
  eissn       = {{1568-5535}},
  file        = {Gui2015.pdf:Gui2015.pdf:PDF},
  issn        = {{0169-1864}},
  times-cited = {{0}},
  unique-id   = {{ISI:000363030000001}},
}

@InProceedings{Bloesch2015,
  author       = {Bloesch, Michael and Omari, Sammy and Hutter, Marco and Siegwart, Roland},
  title        = {Robust visual inertial odometry using a direct EKF-based approach},
  booktitle    = {Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on},
  year         = {2015},
  pages        = {298--304},
  organization = {IEEE},
  file         = {Bloesch2015.pdf:Bloesch2015.pdf:PDF},
  owner        = {cyang},
  timestamp    = {2016.09.13},
}

@Article{Li2013,
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  file        = {Li2013.pdf:Li2013.pdf:PDF},
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@InProceedings{Huang2014,
  author            = {Huang, Guoquan and Kaess, Michael and Leonard, John J.},
  title             = {Towards Consistent Visual-Inertial Navigation},
  booktitle         = {2014 IEEE International Conference on Robotics and Automation (icra)},
  year              = {{2014}},
  series            = {{IEEE International Conference on Robotics and Automation ICRA}},
  pages             = {{4926-4933}},
  note              = {{IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, PEOPLES R CHINA, MAY 31-JUN 07, 2014}},
  book-group-author = {{IEEE}},
  file              = {Huang2014.pdf:Huang2014.pdf:PDF},
  isbn              = {{978-1-4799-3685-4}},
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@Comment{jabref-meta: databaseType:bibtex;}