- RTAB-Map's page at IntRoLab
- Papers
- Similar projects: Find-Object -
- To help me keeping this project updated:
+ -
+
To help me keeping this project updated:
+ +
![\"RTAB-Map](\"https://raw.githubusercontent.com/introlab/rtabmap/master/guilib/src/images/RTAB-Map.png\" "\\"RTAB-Map\\"")
\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![\"ROS\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/ros.png\")
![\"Ubuntu\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/ubuntu.png\")
![\"Mac](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/apple.png\")
![\"Windows\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/windows.png\")
![\"Google](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/tango.png\")
![\"Raspberry](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/logos/raspberrypi.png\")
\r\n\r\n\r\n * [Installation](https://github.com/introlab/rtabmap/wiki/Installation) instructions. \r\n * [Tutorials](https://github.com/introlab/rtabmap/wiki/Tutorials).\r\n * [Tools](https://github.com/introlab/rtabmap/wiki/Tools).\r\n * For **ROS** users, take a look to [rtabmap](http://wiki.ros.org/rtabmap) page on the ROS wiki for a package overview. See also [SetupOnYourRobot](http://wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot) to know how to integrate RTAB-Map on your robot.\r\n\r\n### Troubleshooting\r\n**Standalone**\r\n\r\n * Visit the [wiki](https://github.com/introlab/rtabmap/wiki).\r\n * Ask a question on the [RTAB-Map Forum](http://official-rtab-map-forum.67519.x6.nabble.com/).\r\n * Post an [issue on GitHub](https://github.com/introlab/rtabmap/issues) \r\n * For the loop closure detection approach, visit [RTAB-Map on IntRoLab website](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map)\r\n\r\n**ROS**\r\n\r\n * Visit [rtabmap_ros](http://wiki.ros.org/rtabmap_ros) wiki page for nodes documentation, demos and tutorials on ROS. \r\n * Ask a question on [answers.ros.org](http://answers.ros.org/questions/scope:all/sort:activity-desc/tags:rtabmap_ros/page:1/) with **rtabmap** or **rtabmap_ros** tag.\r\n\r\n## License\r\n * If OpenCV is built **without the nonfree** module, RTAB-Map can be used under the permissive BSD License.\r\n * If OpenCV is built **with the nonfree** module, RTAB-Map is free for research only because it depends on **SURF** and **SIFT** features. **SIFT** and **SURF** are not free for commercial use.\r\n * SURF noncommercial notice: http://www.vision.ee.ethz.ch/~surf/download.html\r\n * SIFT patent: http://www.cs.ubc.ca/~lowe/keypoints/\r\n\r\n## Author\r\n * [Mathieu Labbé](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php?title=Mathieu_Labbé&setlang=en)\r\n * [RTAB-Map's page at IntRoLab](http://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map)\r\n * [Papers](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map#Publications)\r\n * Similar projects: [Find-Object](http://introlab.github.io/find-object/)\r\n * To help me keeping this project updated: [](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=X8TCXXHHDL62Q)\r\n\r\n## What's new \r\n\r\n### October 2016\r\n\r\n * **Version 0.11.11**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.11) for more info!\r\n\r\n### July 2016\r\n\r\n * **Version 0.11.8**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.8) for more info!\r\n\r\n### June 2016\r\n\r\n * **Version 0.11.7**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.7) for more info!\r\n\r\n\r\n### February 2016\r\n\r\n * I'm pleased to announce that RTAB-Map is now on **Project Tango**. The app is [available](https://play.google.com/store/apps/details?id=com.introlab.rtabmap) on Google Play Store.\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/rtabmap-tango.jpeg\" "\\"video\\"")
\r\n\r\n * Screenshots:\r\n\r\n ![\"rtabmap](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/rtabmap-tango.png\")
\r\n\r\n ![\"rtabmap](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/rtabmap-tango2.png\")
\r\n\r\n### October 2015\r\n\r\n * **Version 0.10.10**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.10.10) for more info!\r\n\r\n### September 2015\r\n\r\n * **Version 0.10.6**: Integration of a robust graph optimization approach called Vertigo (which uses [g2o](https://openslam.org/g2o.html) or [GTSAM](https://collab.cc.gatech.edu/borg/gtsam)), see [this page](https://github.com/introlab/rtabmap/wiki/Robust-Graph-Optimization):\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/robust_graph_optimization.jpg\" "\\"video\\"")
\r\n\r\n### August 2015\r\n\r\n * **Version 0.10.5**: New example to export data to [MeshLab](http://meshlab.sourceforge.net/) in order to add textures on a created mesh with low polygons, see [this page](https://github.com/introlab/rtabmap/wiki/Export-Raster-Layers-to-MeshLab):\r\n\r\n ![\"Texture](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/Tutorials/Texture/texture_tutorial.jpeg\")
\r\n\r\n### October 2014\r\n\r\n * New example to speed up RTAB-Map's odometry, see [this page](https://github.com/introlab/rtabmap/wiki/Change-parameters):\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/speedup.jpeg\" "\\"video\\"")
\r\n\r\n### September 2014\r\n\r\n * At **IROS 2014** in Chicago, a team using RTAB-Map for SLAM **won** the Kinect navigation contest held during the conference. See their press release for more details: [Winning the IROS2014 Microsoft Kinect Challenge](http://www.meetup.com/SV-ROS-users/pages/Winning_the_IROS2014_Microsoft_Connect_Challenge/). I also added the Wiki page [IROS2014KinectChallenge](https://github.com/introlab/rtabmap/wiki/IROS-2014-Kinect-Challenge) showing in details the RTAB-Map part used in their solution.\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/iros2014.jpeg\" "\\"video\\"")
\r\n\r\n### August 2014\r\n\r\n * Here a comparison between reality and what can be shown in RVIZ (you can [reproduce this demo here](http://wiki.ros.org/rtabmap_ros#Robot_mapping_with_Find-Object)):\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/findobject.jpeg\" "\\"video\\"")
\r\n\r\n### July 2014\r\n\r\n * Added [Setup on your robot](http://wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot) wiki page to know how to integrate RTAB-Map on your ROS robot. Multiple sensor configurations are shown but the optimal configuration is to have a 2D laser, a Kinect-like sensor and odometry.\r\n\r\n ![\"AZIMUT3\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/Tutorials/MultiSession/4.png\")
\r\n\r\n Onboard mapping | Remote mapping\r\n------------ | -------------\r\n![\"\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/rgbd/setupA.png\")
| ![\"\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/rgbd/remoteMapping.png\")
\r\n\r\n### June 2014\r\n\r\n * I'm glad to announce that my paper submitted to [IROS 2014](http://www.iros2014.org/) was accepted! [This paper](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/images/e/eb/Labbe14-IROS.pdf) explains in details how RGB-D mapping with RTAB-Map is done. Results shown in this paper can be reproduced by the [Multi-session mapping](https://github.com/introlab/rtabmap/wiki/Multi-session) tutorial:\r\n\r\n ![\"Multi-session](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/Tutorials/MultiSession/3.png\")
\r\n\r\n\r\n## Videos\r\n\r\n * **RGBD-SLAM**\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/desktop.jpeg\" "\\"video\\"")
\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/globalonly.jpeg\" "\\"video\\"")
\r\n\r\n * **Appearance-based loop closure detection**\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/rtabmap.jpeg\" "\\"video\\"")
\r\n\r\n ![\"video\"](\"https://raw.githubusercontent.com/wiki/introlab/rtabmap/doc/video_screenshots/newcollegeomni.jpeg\" "\\"video\\"")
\r\n\r\n * More loop closure detection videos [here](http://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map).",
+ "body": "\r\n[](http://www.youtube.com/watch?v=AMLwjo80WzI)\r\n\r\n## Overview \r\n\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 \r\n\r\n\r\n * [Installation](https://github.com/introlab/rtabmap/wiki/Installation) instructions. \r\n * [Tutorials](https://github.com/introlab/rtabmap/wiki/Tutorials).\r\n * [Tools](https://github.com/introlab/rtabmap/wiki/Tools).\r\n * For **ROS** users, take a look to [rtabmap](http://wiki.ros.org/rtabmap) page on the ROS wiki for a package overview. See also [SetupOnYourRobot](http://wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot) to know how to integrate RTAB-Map on your robot.\r\n\r\n### Troubleshooting\r\n**Standalone**\r\n\r\n * Visit the [wiki](https://github.com/introlab/rtabmap/wiki).\r\n * Ask a question on the [RTAB-Map Forum](http://official-rtab-map-forum.67519.x6.nabble.com/).\r\n * Post an [issue on GitHub](https://github.com/introlab/rtabmap/issues) \r\n * For the loop closure detection approach, visit [RTAB-Map on IntRoLab website](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map)\r\n\r\n**ROS**\r\n\r\n * Visit [rtabmap_ros](http://wiki.ros.org/rtabmap_ros) wiki page for nodes documentation, demos and tutorials on ROS. \r\n * Ask a question on [answers.ros.org](http://answers.ros.org/questions/scope:all/sort:activity-desc/tags:rtabmap_ros/page:1/) with **rtabmap** or **rtabmap_ros** tag.\r\n\r\n## License\r\n * If OpenCV is built **without the nonfree** module, RTAB-Map can be used under the permissive BSD License.\r\n * If OpenCV is built **with the nonfree** module, RTAB-Map is free for research only because it depends on **SURF** and **SIFT** features. **SIFT** and **SURF** are not free for commercial use.\r\n * SURF noncommercial notice: http://www.vision.ee.ethz.ch/~surf/download.html\r\n * SIFT patent: http://www.cs.ubc.ca/~lowe/keypoints/\r\n\r\n## Author\r\n * [Mathieu Labbé](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php?title=Mathieu_Labbé&setlang=en)\r\n * [RTAB-Map's page at IntRoLab](http://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map)\r\n * [Papers](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map#Publications)\r\n * Similar projects: [Find-Object](http://introlab.github.io/find-object/)\r\n * To help me keeping this project updated: \r\n\r\n [](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=X8TCXXHHDL62Q)\r\n\r\n## What's new \r\n\r\n### October 2016\r\n\r\n * **Version 0.11.11**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.11) for more info!\r\n\r\n### July 2016\r\n\r\n * **Version 0.11.8**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.8) for more info!\r\n\r\n### June 2016\r\n\r\n * **Version 0.11.7**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.11.7) for more info!\r\n\r\n\r\n### February 2016\r\n\r\n * I'm pleased to announce that RTAB-Map is now on **Project Tango**. The app is [available](https://play.google.com/store/apps/details?id=com.introlab.rtabmap) on Google Play Store.\r\n\r\n \r\n\r\n * Screenshots:\r\n\r\n \r\n\r\n \r\n\r\n### October 2015\r\n\r\n * **Version 0.10.10**: Visit the [release page](https://github.com/introlab/rtabmap/releases/0.10.10) for more info!\r\n\r\n### September 2015\r\n\r\n * **Version 0.10.6**: Integration of a robust graph optimization approach called Vertigo (which uses [g2o](https://openslam.org/g2o.html) or [GTSAM](https://collab.cc.gatech.edu/borg/gtsam)), see [this page](https://github.com/introlab/rtabmap/wiki/Robust-Graph-Optimization):\r\n\r\n \r\n\r\n### August 2015\r\n\r\n * **Version 0.10.5**: New example to export data to [MeshLab](http://meshlab.sourceforge.net/) in order to add textures on a created mesh with low polygons, see [this page](https://github.com/introlab/rtabmap/wiki/Export-Raster-Layers-to-MeshLab):\r\n\r\n \r\n\r\n### October 2014\r\n\r\n * New example to speed up RTAB-Map's odometry, see [this page](https://github.com/introlab/rtabmap/wiki/Change-parameters):\r\n\r\n \r\n\r\n### September 2014\r\n\r\n * At **IROS 2014** in Chicago, a team using RTAB-Map for SLAM **won** the Kinect navigation contest held during the conference. See their press release for more details: [Winning the IROS2014 Microsoft Kinect Challenge](http://www.meetup.com/SV-ROS-users/pages/Winning_the_IROS2014_Microsoft_Connect_Challenge/). I also added the Wiki page [IROS2014KinectChallenge](https://github.com/introlab/rtabmap/wiki/IROS-2014-Kinect-Challenge) showing in details the RTAB-Map part used in their solution.\r\n\r\n \r\n\r\n### August 2014\r\n\r\n * Here a comparison between reality and what can be shown in RVIZ (you can [reproduce this demo here](http://wiki.ros.org/rtabmap_ros#Robot_mapping_with_Find-Object)):\r\n\r\n \r\n\r\n### July 2014\r\n\r\n * Added [Setup on your robot](http://wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot) wiki page to know how to integrate RTAB-Map on your ROS robot. Multiple sensor configurations are shown but the optimal configuration is to have a 2D laser, a Kinect-like sensor and odometry.\r\n\r\n \r\n\r\n Onboard mapping | Remote mapping\r\n------------ | -------------\r\n | \r\n\r\n### June 2014\r\n\r\n * I'm glad to announce that my paper submitted to [IROS 2014](http://www.iros2014.org/) was accepted! [This paper](https://introlab.3it.usherbrooke.ca/mediawiki-introlab/images/e/eb/Labbe14-IROS.pdf) explains in details how RGB-D mapping with RTAB-Map is done. Results shown in this paper can be reproduced by the [Multi-session mapping](https://github.com/introlab/rtabmap/wiki/Multi-session) tutorial:\r\n\r\n \r\n\r\n\r\n## Videos\r\n\r\n * **RGBD-SLAM**\r\n\r\n \r\n\r\n \r\n\r\n * **Appearance-based loop closure detection**\r\n\r\n \r\n\r\n \r\n\r\n * More loop closure detection videos [here](http://introlab.3it.usherbrooke.ca/mediawiki-introlab/index.php/RTAB-Map).",
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