北京科技大学学报Issue(6)：826-830,5.
基于混沌粒子群--专用遗传算法切换策略的移动机器人路径规划
Switch strategy based on chaos particle swarm optimization and spe-cialized genetic algorithm for path planning of mobile robots
摘要
Abstract
A switching strategy based on chaos particle swarm optimization and specialized genetic algorithm (CPSO-SGA) was presented by combining their own advantages. In the switching strategy, CPSO is applied in the former step and SGA is executed in the later step. The best switching conditions under three switching indices of iteration steps, population standard deviation, and optimal individual fitness values were determined by large amounts of simulation experiments. In comparison with single SGA and single CPSO, the proposed switching strategy CPSO-SGA has a better performance when path length, smoothness, and running time are taken into consideration.关键词
移动机器人/路径规划/粒子群算法/遗传算法/切换Key words
mobile robots/path planning/particle swarm optimization/genetic algorithms/switching分类
计算机与自动化引用本文复制引用
张超,李擎,董冀媛,韩彩卫,刘启晗..基于混沌粒子群--专用遗传算法切换策略的移动机器人路径规划[J].北京科技大学学报,2013,(6):826-830,5.基金项目
教育部第36批留学回国人员科研启动基金资助项目(1341)；国家自然科学基金资助项目(60374032)；北京市重点学科建设资助项目(XK100080537) （1341）
