An improved gravitational search algorithm and its performance analysis for multi-robot path planning

This paper proposes a new methodology to optimize trajectory of the path for multi-robots using Improved Gravitational Search Algorithm (IGSA) in clutter Environment. IGSA technique is incorporated into the multi-robot system in a dynamic framework, which will provide robust performance, self-deterministic cooperation, and coping with an inhospitable environment. The robots on the team make independent decisions, coordinate, and cooperate with each other to accomplish a common goal using the developed IGSAs. A path planning scheme has been developed using IGSA to optimally obtain the succeeding positions of the robots from the existing position in the proposed environment. Finally, the analytical and experimental result of the multi-robot path planning were compared with those obtained by IGSA, ABC (Artificial Bee Colony) and DE (Differential Evolution) in a similar environment. The simulation and the Khepera environment result show outperforms of IGSA as compared to ABC and DE with respect to the average total trajectory path deviation and average uncovered trajectory target distance.