Research of biogeography particle swarm optimization for robot path planning

Global path planning of mobile robot in a static environment is one of the most important problems in the field of mobile robot. Biogeography-based Optimization (BBO) is a relative new algorithm inspired by biogeography. It mainly uses the biogeography-based migration operator to share the information among solutions. Particle swarm optimization (PSO) is a classical heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. This paper presents a new method of global path planning by combining BBO, PSO and approximate voronoi boundary network (AVBN) in a static environment. The idea of this paper is to apply position updating strategy of PSO to increase the diversity of population in BBO and then use the obtained biogeography particle swarm optimization algorithm (BPSO) to optimize the paths in path network obtained by AVBN modeling. Experimental results in simulation show that the proposed method is feasible and effective.