Real-Time Obstacle Avoidance Method for Mobile Robots Based on a Modified Particle Swarm Optimization

Abstract

A novel method for the robot path planning in dynamic environment is presented in this paper. Based on the analysis of visual modeling, the reason of premature convergence and diversity loss in PSO is explained, and a new modified algorithm is proposed to ensure the rational flight of every particle dimensional component. Meanwhile, two parameters of particle-distribution-degree and particle dimension-distance are introduced into the proposed algorithm in order to avoiding premature convergence. Simulation results show that it has better ability of finding global optimum, and still is more efficient than traditional particle swarm optimization and genetic algorithm (GA).