吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (6): 998-1006.

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基于改进人工势场法的路径规划研究 

 谢春丽, 陶天艺, 李佳浩    

  1. 东北林业大学 机电工程学院, 哈尔滨 150006
  • 收稿日期:2023-03-27 出版日期:2023-11-30 发布日期:2023-12-01
  • 通讯作者: 陶天艺(1995— ), 男, 哈尔滨人, 东北林业大学硕士研究生, 主要从事智能机器人路径规划 研究, (Tel)86-15604590627 E-mail:1017096270@ qq. com
  • 作者简介:谢春丽(1978— ), 女, 吉林镇赉人, 东北林业大学副教授, 主要从事车辆控制研究, (Tel)86-15244677420(E-mail) xcl08 @ 126. com
  • 基金资助:
    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)

Research on Path Planning Based on Improved Artificial Potential Field Method

 XIE Chunli, TAO Tianyi, LI Jiahao   

  1. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150006, China
  • Received:2023-03-27 Online:2023-11-30 Published:2023-12-01

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。

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 

Abstract: 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.

Key words: artificial potential field method, mobile robot, path planning, local minimum, safety distance factor, U-shaped obstacle

中图分类号: 

  • TP301. 6