Path optimization for cooperative mapping with multiple-agents

Abstract

When a mobile robot performs a mapping mission, the selected path and the number of robots have a significant effect on its mission performance. This study addresses the problem of obtaining the optimal path to conduct the mapping mission through multi-robot systems, and it aims to ensure efficient mapping by activating the cooperative aspect. To achieve the cooperative aspect of the multi-robot systems, it is necessary to make a path plan wherein each robot considers better configuration based on the current sensing results. To this end, a Fisher information matrix that can estimate position uncertainty and calculate the effect of robots' configuration was used. To further consider temporal effects, a simple approach to calculate the convergence rate over the time of uncertainty is presented, and an improved path planning algorithm is proposed. The proposed algorithm was simulated and compared with other path planning algorithms, that led to performance evaluation.