Simultaneous Localisation And Mapping (SLAM)



As robots are exploring uncharted areas, they must deal with the unknown. Navigating the unknown can kidnap robots or have critical consequences. Simultaneous localisation and mapping (SLAM) is a powerful concept for mapping and reliably localise the robot in the unknown. This paper Simultaneous localisation and mapping with ROS tests a ROS based graph-based SLAM multi-session mapping approach that can handle diverse and large environments with under 0.9m error in over 400m of explored environments.


The paper accompanying code can be found here. The pre-mapped environment databases can be found here.


A video of SLAM in action can be viewed below.




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