基于改进人工势场法的路径规划研究  

Research on Path Planning Based on Improved Artificial Potential Field Method

作　　者：谢春丽 陶天艺 李佳浩 XIE Chunli;TAO Tianyi;LI Jiahao(College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150006,China)

机构地区：[1]东北林业大学机电工程学院,哈尔滨150006

出　　处：《吉林大学学报（信息科学版）》2023年第6期998-1006,共9页Journal of Jilin University（Information Science Edition）

基　　金：黑龙江省自然科学基金资助项目(LH2021F002);大学生创新训练基金资助项目(202210225441)。

摘　　要：针对传统的人工势场法在移动机器人路径规划中存在的目标不可达和局部极小值问题,提出了一种改进的人工势场法。首先,对目标点附近有障碍物时由于斥力较大,机器人难以到达目标点的问题,在势场中引入了安全距离因子,并对该参数进行了优化,从而使机器人与障碍物保持合适的距离,顺利到达目标点。其次,为解决局部极小值问题,引入了局部极小值判别条件,并在触发该条件时对局部极小区域进行绕行,使机器人顺利到达目标点。仿真结果表明,改进后的算法在不同数量的障碍物地图环境下运行,有较强的鲁棒性,所提出的算法可以使机器人在U型障碍物环境中绕过局部极小值区域,成功解决了移动机器人路径规划中的局部极小值问题。An improved artificial potential field method is proposed to solve the problems of local minimum and unable to reach the target in the path planning of mobile robots.Firstly,in order for the robot to reach the target point when there are obstacles near the target point due to the large repulsive force,a safe distance factor is introduced into the potential field,and this parameter is optimized,so that the robot can maintain a proper distance from the obstacles and reach the target point smoothly.Secondly,in order to solve the local minimum problem,the local minimum discriminant condition is introduced,and the local minimum region is circum-navigated when the condition is triggered,so that the robot can reach the target point smoothly.The simulation results show that the improved algorithm has strong robustness when operating in the map environment with different number of obstacles.The proposed algorithm can make the robot bypass the local minimum area in the U-shaped obstacle environment,and successfully solve the local minimum problem in the mobile robot path planning.

关 键 词：人工势场法 移动机器人 路径规划 局部极小值 安全距离因子 U型障碍物 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]