Cooperative simultaneous localization and mapping for multi-robot: Approach & experimental validation

This paper focuses the multi-robot cooperative simultaneous localization and mapping (SLAM) problem. First, we proposed a decoupled fashion of the map building. Through this fashion, each robot builds the local sub-map independently. The sub-map fusion approach based on Extended Kalman Filter (EKF) is provided. Second, we implemented the active motion of each robot during the local sub-map building process. Each robot will choose the optimized control input of the next step. The optimal objective for this paper is to address the accuracy, the information gain, and the multi-robots cooperation. Finally, an experiment system called IIPSLAMPlatform is built to implement the multi-robot cooperative map building. The IIPSLAMPlatform is built in hybrid architecture. The experiments are conducted under this experiment system. We also compared the multi-robot map building with the single robot condition from the view of uncertainty. The result shows the advantage of multi-robot map building.