Path planning algorithm of mobile robot based on particle swarm optimization
HAN Ming1,2, LIU Jiaomin2, WU Shuomei1, WANG Jingtao1
1. College of Computer Science and Engineering, Shijiazhuang University, Shijiazhuang Hebei 050035, China; 2. School of Information Science and Engineering, Yanshan University, Qinhuangdao Hebei 066004, China
Abstract:Concerning the slow convergence and local optimum of the traditional robot path planning algorithms in complicated enviroment, a new path planning algorithm for mobile robots based on Particle Swarm Optimization (PSO)algorithm in repulsion potential field was proposed. Firstly, the grid method was used to give a preliminary path planning of robot, which was regarded as the initial particle population. The size of grids was determined by the obstacles of different shapes and sizes and the total area of obstacles in the map, then mathematical modeling of the planning path was completed. Secondly, the particle position and speed were constantly updated through the cooperation between particles. Finally, the high-security fitness function was constructed using the repulsion potential field of obstacles to obtain an optimal path from starting point to target of robot. Simulation experiment was carried out with Matlab. The experimental results show that the proposed algorithm can implement path optimization and safely avoid obstacles in a complex environment; the contrast experimental results indicat that the proposed algorithm converges fast and can solve the local optimum problem.
韩明, 刘教民, 吴朔媚, 王敬涛. 粒子群优化的移动机器人路径规划算法[J]. 计算机应用, 2017, 37(8): 2258-2263.
HAN Ming, LIU Jiaomin, WU Shuomei, WANG Jingtao. Path planning algorithm of mobile robot based on particle swarm optimization. Journal of Computer Applications, 2017, 37(8): 2258-2263.
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