An improved particle swarm optimization for multi-robot path planning

Abstract

This paper proposes a new methodology to optimize trajectory of the path for multi-robots using Improved particle swarm optimization Algorithm (IPSO) in clutter Environment. IPSO 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 IPSO. A path planning scheme has been developed using IPSO 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 IPSO, PSO and DE (Differential Evolution) in a similar environment. The simulation and the Khepera environment result show outperforms of IPSO as compared to PSO and DE with respect to the average total trajectory path deviation and average uncovered trajectory target distance.