摘要
描绘了排爆机器人路径规划问题,提出了混合混沌序列与遗传算法的排爆机器人路径规划算法。针对遗传算法易于陷入局部收敛,在寻优过程中易于出现抖振,算法收敛精度不高等问题,在遗传算法中引入Logistic混沌序列,生成与机器人路径选择更加匹配的优化算法。运用MATLAB进行算法仿真,分析比较经典遗传算法和优化后的算法。仿真结果显示,算法优化后机器人行走路径更加合理,算法的收敛精度提高。
This paper describes the path planning problem of explosive disposal(EOD) robot,and proposes the path planning algorithm with hybrid chaotic sequence and genetic algorithm.Aiming at the problem that genetic algorithm is easy to fall into local convergence,it is prone to chattering in the optimization process,and the convergence accuracy of the algorithm is not high. Logistic chaotic sequences are introduced into the genetic algorithm to generate an optimized algorithm which is more suitable for robot path selection.MATLAB is used to simulate the algorithm,analyze and compare the classical genetic algorithm and the optimized algorithm,the simulation results show that the walking path of the robot with optimized algorithm is more reasonable and the convergence accuracy of the algorithm is improved.
作者
殷新凯
茅健
周玉凤
陈晓平
Yin Xinkai;Mao Jian;Zhou Yufeng;Chen Xiaoping(Shanghai University of Engineering Science,School of Mechanical and Automotive Engineering,Shanghai 201620,China;Ningbo University of Technology,Hangzhou Bay Automotive Institute)
出处
《计算机时代》
2019年第7期5-8,共4页
Computer Era
