Obstacle Avoidance for Multi-agent Path Planning Based on Vectorized Particle Swarm Optimization

摘要

This paper deals with an approach to path planning by obstacle avoidancefor multi-agent systems. An effective framework is presented based on theParticle Swarm Optimization (PSO) method; an evolutionary computation(EC) technique that uses the dynamics of the swarm to search the solutions for theoptimization problems. It describes the path replanning technique and obstacleavoidance for autonomous multi-agent systems. A simultaneous replanning conceptis incorporated into the path planning to avoid both static and dynamic obstacles.This proposed algorithm reduces the computational time of the path planning. In thedynamic environment, the numerical results show that the Simultaneous ReplanningVectorized Particle Swarm Optimization (SRVPSO) algorithm is effective andalso efficient for multi-agent systems.