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## repository: https://github.com/introlab/rtabmap
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== 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, and/or on a robot equipped with a laser rangefinder for 3DoF mapping (2D LiDAR) and 6DoF mapping (3D LiDAR).

<<Youtube(o1GSQanY-Do)>>

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 [[https://github.com/introlab/rtabmap/wiki|RTAB-Map's wiki]] to know how to use the standalone application and [[https://github.com/introlab/rtabmap/wiki/Tools|tools]] that come with this package:
 {{{
$ rtabmap
}}} 

== Citing ==
If you use [[rtabmap]] in academic context, please cite the appropriate publication from http://introlab.github.io/rtabmap
 
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