机器人与自动化的进步

Hybrid Gravity Gradient Inversion-PSO algorithm for Motion Planning of Mobile Robots

Abstract

Meng Wu and Lihua Yang

Motion planning is a common task required to be fulfilled by robots. A novel strategy combining particle swarm optimization and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. Particle Swarm Optimization (PSO) is employed to do motion planning and fitness function in PSO is built based on gravity gradient inversion algorithm. The relative distance and orientation between each particle and the center of an obstacle is calculated by gravity gradient inversion algorithm, then, a fitness function is built based on the distance and orientation. The proposed strategy is validated by the simulation and experiment results.