A Novel Poly-clone Particle Swarm Optimization Algorithm and Its Application in Mobile Robot Path Planning
Particle swarm optimization (PSO) algorithm is a new random global optimization algorithm, and the simple PSO algorithm (SPSOA) is short of high convergence speed, strong optimization ability and so on. To improve the optimization ability of SPSOA, the clonal copy, clonal crossover, hyper-mutation and clonal selection are introduced in the SPSOA, and a novel poly-clone particle swarm optimization algorithm (PCPSOA) is presented. Compared with the corresponding SPSOA and inertia weight PSO algorithm (IWPSOA), the simulation results of some complex functions optimization indicate that the proposed PCPSOA is characterized by strong searching ability and quick convergence speed. Finally, the PCPSOA is introduced into the path planning of mobile robot and the global path is optimized using PCPSOA on the basis of MAKLINK graph. The simulation results show that the path planning based on PCPSOA is feasible and effective.
Particle Swarm Optimization Clonal Selection Path Planning MAKLINK Graph
Yi Shen Mingxin Yuan
School of Mechanical and Metallurgical Engineering, Jiangsu University of Science and Technology, Zhangjiagang 215600, China
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
2271-2276
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）