"body":"\r\n[](http://www.youtube.com/watch?v=AMLwjo80WzI)\r\n\r\n## Overview \r\n<img src=\"https://raw.githubusercontent.com/introlab/rtabmap/master/guilib/src/images/RTAB-Map.png\" alt=\"RTAB-Map logo\" title=\"RTAB-Map\" align=\"left\" width=\"120\">\r\n**RTAB-Map** (Real-Time Appearance-Based Mapping) is a RGB-D Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determinate how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map's graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to limit the number of locations used for loop closure detection and graph optimization, so that real-time constraints on large-scale environnements are always respected. RTAB-Map can be used alone with a hand-held Kinect or stereo camera for 6DoF RGB-D mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping.\r\n * **RGB-D mapping**\r\n * M. Labbé and F. Michaud, “[Online Global Loop Closure Detection for Large-Scale Multi-Session Graph-Based SLAM](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/images/e/eb/Labbe14-IROS.pdf),” in _Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems_, 2014. ([IEEE Xplore](http://ieeexplore.ieee.org/document/6942926/))\r\n * Results shown in this paper can be reproduced by the [Multi-session mapping](https://github.com/introlab/rtabmap/wiki/Multi-session) tutorial.\r\n * **Loop closure detection**:\r\n * M. Labbé and F. Michaud, “[Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/images/b/bc/TRO2013.pdf),” in _IEEE Transactions on Robotics_, vol. 29, no. 3, pp. 734-745, 2013. ([IEEE Xplore](http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6459608))\r\n * M. Labbé and F. Michaud, “[Memory management for real-time appearance-based loop closure detection](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/images/f/f0/Labbe11memory.pdf),” in _Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems_, 2011, pp. 1271–1276. ([IEEE Xplore](http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6094602))\r\n * Visit [RTAB-Map's page on IntRoLab](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map) for detailed information on the loop closure detection approach and related datasets.\r\n\r\n## Install \r\n<a href=\"https://github.com/introlab/rtabmap_ros#rtabmap_ros\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/ros.png\" alt=\"ROS\" width=\"50\"></a> <a href=\"https://github.com/introlab/rtabmap/wiki/Installation#ubuntu\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/ubuntu.png\" alt=\"Ubuntu\" width=\"50\"></a> <a href=\"https://github.com/introlab/rtabmap/wiki/Installation#macosx\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/apple.png\" alt=\"Mac OS X\" width=\"50\"></a> <a href=\"https://github.com/introlab/rtabmap/wiki/Installation#windows\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/windows.png\" alt=\"Windows\" width=\"50\"></a> <a href=\"https://play.google.com/store/apps/details?id=com.introlab.rtabmap\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/tango.png\" alt=\"Google Tango\" width=\"50\"></a> <a href=\"https://github.com/introlab/rtabmap/wiki/Installation#raspberrypi\"><img src=\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/raspberrypi.png\" alt=\"Raspberry Pi\" width=\"40\"></a>\r\n\r\n\r\n * [Installation](https://github.com/introlab/rtabmap/wiki/Installation) instructions. \r\n * [Tutorials](https://github.com/introlab/rtabmap/wiki/
