A Specialized Particle Swarm Optimization for global path planning of mobile robots

Abstract

A specialized global path planning algorithm for mobile robot based on Guaranteed Convergence Particle Swarm Optimization (GCPSO) is proposed. An environmental map was set up and a path connecting the start node and the goal node was coded as a particle. Then, a particular “active region” for particles was mapped out according to the location of obstacles. The initial particle population was generated within this region and particles flied in the “active region” to search for the optimum path. In the search process, both acceleration coefficients and inertia weight of particle swarm optimization algorithm are self-adaptively adjusted and invalid particles are replaced by global optima or local optima in the adjacent area. The simulation studies in both simple environment and complicated environment are carried out and the simulation results show that the proposed algorithm has advantages such as faster search speed and higher search quality.