摘要
针对机器人路径规划中,应用遗传算法时容易陷入局部最优解以及收敛速度较慢等问题,设计出一种基于混沌遗传算法的路径规划方法。在基本遗传算法的基础上采用自适应调整的选择概率,并引入混沌操作,从而增强移动机器人路径规划算法的鲁棒性,解决一般遗传算法的早熟和收敛速度慢问题。经MATLAB仿真,证明该方法具有良好的避障性能。
In order to solve the problems of easily getting into part extremum and slowly converging to an optimum in using genetic algorithm for robot path planning, a path planning method for robot based on chaos genetic algorithm is designed, using self adapting selection probability and adding chaos algorithm improve the simple genetic algorithm, thereby the path ptanning method for robot is more robust and the problems of early and slowly convergence of simple genetic algorithm is solved. MATLAB simulation prove the good performance of obstacle avoidance of this method.
出处
《微型机与应用》
2011年第13期69-71,共3页
Microcomputer & Its Applications
关键词
混沌
遗传算法
路径规划
chaos
genetic algorithm
path planning
