Local vs. global: Indoor multi-robot simultaneous localization and mapping in wireless sensor networks

The multi-robot SLAM or cooperative SLAM (CSLAM) by multiple robots, both local based and global based, in a RF wireless sensor network, is investigated in detail in this paper. We propose a new multi-robot SLAM approach, the localization is done by using trilateration localization method, and we use cooperative compressive sensing to build map with sparse information acquired by robots. We make an evaluation between the current baseline algorithms and our proposed method. The comparison result implies that particle filter is more robust while our approach could be more feasible dealing with the environment where either little prior knowledge about the sensed field is available.