摘要
传统人工势场法在移动机器人导航过程中存在局部极小值,障碍物周围震荡等问题。针对采用传统人工势场法实现移动机器人导航过程中存在的问题,本文引入旋转力改进人工势场法,同时运用细菌觅食混合粒子群算法(BF-PSO)对移动机器人导航过程中的控制器参数及势场函数增益系数进行离线优化。运用优化参数进行基于改进人工势场法的移动机器人导航的仿真,仿真结果表明BF-PSO算法对移动机器人导航具有较好的优化效果。
The traditional artificial potential field method has some problems in the navigation of mobile robot, such as local minimum and turbulence around the obstacle. In view of these problems, this paper introduced the rotating force im- proved artificial potential field method, and the bacterial foraging hybrid particle swarm algorithm was used to off-line optimize controller parameters and gain coefficient of potential field function in navigation of mobile robot. The simulation of mobile robot navigation based on improved artificial potential field using optimization parameters show that the BF-PSO algorithm has better optimization effect on the navigation of mobile robot.
作者
李国进
陈武
易丐
LI Guoqin CHEN Wu YI Gai(College of Electrical Engineering, Guangxi University, Nanning,Guangxi 530004, Chin)
出处
《计算技术与自动化》
2017年第1期52-56,共5页
Computing Technology and Automation
