rtabmap: rtabmap | rtabmap_ros

  Show EOL distros: 

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Package Summary

RTAB-Map's standalone library. RTAB-Map is a RGB-D SLAM approach with real-time constraints.

Overview

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D Graph SLAM approach based on a global Bayesian 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 or stereo camera for 6DoF RGB-D mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping.

Visit rtabmap_ros to know how to use RTAB-Map under ROS. The rtabmap package is only for convenient release of the RTAB-Map libraries and standalone application. Visit RTAB-Map's wiki to know how to use the standalone application and tools that come with this package:

  • $ rtabmap

Citing

If you use rtabmap in academic context, please cite the following publication:

  • RGBD-SLAM

    • @INPROCEEDINGS{labbe14online, 
        author={Labbe, M. and Michaud, F.}, 
        booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems}, 
        title={{Online Global Loop Closure Detection for Large-Scale Multi-Session Graph-Based SLAM}}, 
        year={2014}, 
        month={Sept}, 
        pages={2661-2666} 
      }

and/or

  • Loop closure detection

    • @ARTICLE{labbe13appearance,
        author = {Labbe, M. and Michaud, F.},
        title = {{Appearance-Based Loop Closure Detection for Online Large-Scale and
              Long-Term Operation}},
        journal = {IEEE Transactions on Robotics},
        year = {2013},
        volume = {29},
        pages = {734-745},
        number = {3}
      }

Wiki: rtabmap (last edited 2018-05-06 20:25:49 by MathieuLabbe)