Pose Graph Map Merging SLAM for Multiple Robots

抄録

In this paper, we present a pose graph map merging SLAM for multiple mobile robot system. The local maps from individual robots are merged in a global framework with little to no latency and the updated maps are sent to all the robots in the network to update the changes in the map. By merging the local maps from the robots, a global representation of the area can be used for different applications The process allows our system for data association and efficient loop closure even for large areas. By combining data from different sensors on the robot, the map merging process is initiated in the back-end while, the local mapping and corrections are done on the robot itself. RGB-D features from the robots are used to detect loop closures and areas in the map that have an overlap and these areas are used to further optimize the graph in the back-end.The proposed system is tested with real robots and the results are discussed.