Growing topological map for SLAM of mobile robots

This paper proposes a simultaneous localization and mapping method in unknown environments of multiple mobile robots. According to the measured distance by laser range finder, a shared map is updated sequentially cooperatively. When the difference between the measured distance and its corresponding map data is large, the robot updates the self-location by using the steady-state genetic algorithm, and updates the map by using topological approach. We propose a map building method using a growing topological map. Finally we discuss the effectiveness of the proposed methods through several experimental results and comparison results.