Path planning of mobile robots based on specialized genetic algorithm and improved particle swarm optimization

Abstract

A specialized genetic algrithm in which initial paths generated by heuristics and the optimum path refined by deletion operator is proposed. PCPSO (parameter chaotic particle swarm optimization) and BICPSO (best individual chaotic particle swarm optimization) are adopted for path planning of mobile robots, and four chaotic mapping models are introduced to discuss the influence on above CPSOs. An improved PSO, BIPSO (best individual particle swarm optimization) based on best individual replacement strategy is proposed, and comparative studies are carried out. The simulation results illustrated that SGA and BIPSO can obtain shorter and smoother path when they are used for path planning of mobile robots.