摘要
人工势场算法是机器人导航中常用的局部路径规划算法,但传统的人工势场算法存在无法到达目标点以及存在局部最小值等问题。本文通过分析人工势场算法的基本原理,并对其进行改善,以提高算法的性能和适应性。首先,本文通过改善人工势场算法的斥力函数,解决了传统算法无法到达目标点的问题;其次,通过提出通过活动窗口判断障碍物是否陷入极小值问题,解决了传统算法存在局部最小值的问题;最后,通过Matlab进行仿真分析,证实上述改善方案可以有效解决人工势场算法存在的问题。本研究将为机器人的自主导航提供重要参考。
The artificial potential field algorithm is a commonly used local path planning algorithm in robot navigation,but the traditional artificial potential field algorithm has problems such as unable to reach the target point and local minimum.In this paper,the basic principle of the artificial potential field method is analyzed and further improved to improve the performance and adaptability of the algorithm.Firstly,this paper solves the problem that the traditional algorithm cannot reach the target point by improving the repulsion function of the artificial potential field algorithm.Secondly,by proposing the problem of judging whether the obstacle falls into the minimum value through the activity window,the problem of local minimum value in the traditional algorithm is solved.Finally,the simulation analysis by Matlab proves that the above improved scheme can effectively solve the problems of artificial potential field algorithm.This study will provide an important reference for autonomous navigation of robots.
作者
何媛媛
唐东林
车健波
王平杰
黄怡丁
张苏洋
He Yuanyuan;Tang Donglin;Che Jianbo;Wang Pingjie;Huang Yiding;Zhang Suyang(Sichuan Special Equipment Inspection and Research Institute,Chengdu,Sichuan 610000;Southwest Petroleum University,Chengdu,Sichuan 610500)
出处
《西部特种设备》
2024年第5期8-14,共7页
Western Special Equipment
关键词
爬壁机器人
机器人导航
仿真分析
Wall-climbing robot
Robot navigation
Simulation analysis
