知识引导遗传算法实现机器人路径规划王雪松.pdf

DOI ：10.13195/j.cd.2009.07.85.wangxs.016 第24 卷第7 期 控 制 与 决 策 2009 年7 月 Vol.24 No.7 Contro l and D e cis ion Jul. 2009 : 1001-0920(2009) 07-1043-07 1, 2 1 1 1 王雪松 , 高 阳, 程玉虎 , 马小平 ( 1. , 221116; 2. a., b., 100190) : 针对传统遗传算法求解机器人路径规划问题存在的收敛速度较 的缺陷, 设计 一种知识引导遗传算法, 在 染色体的编码初始种群的产生各种遗传算子和优化算子中加入相关的领域知识. 综合考虑机器人路径的长度安 全度和平滑度等性能指标, 在对机器人进行路径规划的同时, 利用删除简化修正和平滑4 种优化算子进行路径优 化操作. 仿真结果表明,所提方法能够有效提高遗传算法求解实际路径规划问题的能力和效率. : 遗传算法; 领域知识; 机器人; 路径规划 : TP242 : Knowledge-guided genetic algorithm for path planning of robot 1, 2 1 1 1 WA N G X ue-song , GA O Yang , C H E N G Yu-h u , MA X iao-p i ng ( 1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China; 2a.Institute of utomation, 2b. The Key Laboratory of Complex Systems and Intelligence Science, Chinese cademy of Sciences, Beijing 100190, China. Correspondent: W NG Xue-song, E-mail: wangxuesongcumt@ 163. com) Abstract: In order to improve the convergence speed of traditional genetic algorithm for path planning of robot, a knowledge-guided genetic algorithm is designed by introducing domain knowledge of a path planning problem into the coding of chromosome, initialization of population, genetic operators and optimization operators. The length, safety and smoothness of paths are considered simultaneously during the process of path planning. Four optimization operators, deletion, simplification, modification and smoothness operators, are used to optimize paths searched by the genetic operators. Simulation results show that the proposed method can improve the ability and efficiency of g