基于遗传算法的机器人综合路径规划

J4 ›› 2012, Vol. 30 ›› Issue (3): 228-233.

基于遗传算法的机器人综合路径规划

李艳辉¹,曲萃萃^1|2,赵辉¹

1.东北石油大学电气信息工程学院|黑龙江大庆 163318;2.北京中核东方控制系统工程有限公司研发部|北京 100076

收稿日期:2012-01-09 出版日期:2012-05-24 发布日期:2012-06-08
作者简介:李艳辉（1970—）|女|辽宁法库人|东北石油大学教授|主要从事鲁棒控制、鲁棒滤波和模型降阶研究|（Tel)86-459-6504797 (E-mail)1014441409@qq.com。
基金资助:
黑龙江省教育厅科学技术研究基金资助项目（12511002）

Robot Compositive Path Planning Based on Genetic Algorithm

LI Yan-hui¹,QU Cui-cui^1|2,ZHAO Hui¹

1.College of Electrical and Information Engineering,Northeast Petroleum University,Daqing 163318,China;2.China Naclear Control System Engineering Corporation,Beijing 100076,China

Received:2012-01-09 Online:2012-05-24 Published:2012-06-08

摘要/Abstract

摘要：

为解决机器人路径规划问题，在极坐标系下利用遗传算法，依据多属性决策理论提出了新的综合适应度函数。采用基于该适应度函数的遗传算法可首次规划出满足路径、时间和耗能3个约束属性的最优路径。同时引入理想适应度函数，并基于引入的理想适应度函数，提出一种新的变异算子，该变异算子可保证个体变异的方向性，对优异的父代个体有较小变异、劣质个体有较大变异。仿真结果验证了算法的可行性和有效性。

关键词: 机器人；遗传算法；综合适应度函数；决策理论；多属性；变异算子

Abstract:

We use genetic algorithm to plan robots path in the polar coordinate.A new compositive fitness function based on multiple attribute decision theory is proposed.Using genetic algorithm with this fitness function can plan the optimal path.The path satisfies the constrained attributes of path,time,and energy dissipation optimal.Based on a new introduced perfect fitness function,a new mutation operator is proposed.The advantage of the mutation operator is that it can guarantee the outstanding individual with smaller variable rate,inferior individual with larger variable rate.The simulation results demonstrate the effectiveness and realtime of the proposed algorithm.

Key words: robot, genetic algorithm, compositive fitness function, decision theory;multiple attribute, mutation operator

中图分类号:

TG24

李艳辉, 曲萃萃, 赵辉. 基于遗传算法的机器人综合路径规划[J]. J4, 2012, 30(3): 228-233.

LI Yan-Hui, QU Cui-Cui, DIAO Hui. Robot Compositive Path Planning Based on Genetic Algorithm[J]. J4, 2012, 30(3): 228-233.