Overview

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar 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 handheld Kinect, a stereo camera or a 3D lidar for 6DoF mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping.

Lidar and Visual SLAM

Simultaneous Planning, Localization and Mapping (SPLAM)

Multi-session SLAM

Loop closure detection

Install

Installation instructions.

Tutorials.

Tools.

For ROS users, take a look to rtabmap page on the ROS wiki for a package overview. See also SetupOnYourRobot to know how to integrate RTAB-Map on your robot.

Troubleshooting

Standalone

ROS

Visit rtabmap_ros wiki page for nodes documentation, demos and tutorials on ROS.

Ask a question on answers.ros.org with rtabmap or rtabmap_ros tag.

License

If OpenCV is built without the nonfree module, RTAB-Map can be used under the permissive BSD License.

module, RTAB-Map can be used under the permissive BSD License. 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. SURF noncommercial notice: http://www.vision.ee.ethz.ch/~surf/download.html SIFT patent: http://www.cs.ubc.ca/~lowe/keypoints/

module, RTAB-Map is free for research only because it depends on and features. and are not free for commercial use.

Privacy Policy

RTAB-Map Tango app on Google Play Store requires access to camera to record images that will be used for creating the map. When saving, a database containing these images is created. That database is saved locally on the device (on the sd-card under RTAB-Map folder). While location permission is required to install RTAB-Map Tango, the GPS coordinates are not saved by default, the option “Settings->Mapping…->Save GPS” should be enabled first. RTAB-Map requires read/write access to RTAB-Map folder only, to save, export and open maps. RTAB-Map doesn’t access any other information outside the RTAB-Map folder. RTAB-Map doesn’t share information over Internet unless the user explicitly exports a map to Sketchfab, for which RTAB-Map needs the network. If so, the user will be asked for authorization (oauth2) by Sketchfab (see their Privacy Policy here).

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Author

Mathieu Labbé RTAB-Map’s page at IntRoLab Papers Similar projects: Find-Object If you find this project useful and to help me keeping this project updated, you can buy me a cup of coffee with the link below :P. It is also nice to receive new sensors to test with and even supporting them in RTAB-Map for quick SLAM demonstrations (e.g., stereo cameras, RGB-D cameras, 2D/3D LiDARs). Thanks Stereolabs for the ZED, thanks Walt (with Tango coupon discount) and Google for Google Tango Development Kits and thanks to all contributors (for donations, reporting bugs, helping me fixing bugs or making pull requests).



What’s new

November 2019

AliceVision library has been integrated to RTAB-Map to provide higher texture quality. Compare the updated version of the Ski Cottage on Sketchfab with the old version. Look at how the edges between camera texures are smoother (thx to multi-band blending), decreasing significantly the sharp edge artifacts. Multi-band blending approach can be enabled in File->Export Clouds dialog under Texturing section. RTAB-Map should be built with AliceVision support (CUDA is not required as only texture pipeline is used). A patch is required to avoid problems with Eigen, refer to Docker file here.

September 2017

New version 0.14 of RTAB-Map Tango with GPS support. See it on play store.

July 2017

New version 0.13 of RTAB-Map Tango. See it on play store.

I uploaded a presentation that I did in 2015 at Université Laval in Québec! A summary of RTAB-Map as a RGBD-SLAM approach:

March 2017

February 2017

Version 0.11.14 : Visit the release page for more info! Tango app also updated:

: Visit the release page for more info!

October 2016

Application example: See how RTAB-Map is helping nuclear dismantling with Orano’s MANUELA project (Mobile Apparatus for Nuclear Expertise and Localisation Assistance):

Version 0.11.11: Visit the release page for more info!

July 2016

Version 0.11.8: Visit the release page for more info!

June 2016

Version 0.11.7: Visit the release page for more info!

February 2016

I’m pleased to announce that RTAB-Map is now on Project Tango . The app is available on Google Play Store. Screenshots:



October 2015

Version 0.10.10: Visit the release page for more info!

September 2015

Version 0.10.6: Integration of a robust graph optimization approach called Vertigo (which uses g2o or GTSAM), see this page:

August 2015

Version 0.10.5: New example to export data to MeshLab in order to add textures on a created mesh with low polygons, see this page:

October 2014

New example to speed up RTAB-Map’s odometry, see this page:

September 2014

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. I also added the Wiki page IROS2014KinectChallenge showing in details the RTAB-Map part used in their solution.

August 2014

Here a comparison between reality and what can be shown in RVIZ (you can reproduce this demo here):

July 2014

Added Setup on your robot 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. Onboard mapping Remote mapping

June 2014

I’m glad to announce that my paper submitted to IROS 2014 was accepted! This paper 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 tutorial:

Videos