基于改进人工势场法的移动机器人路径规划

doi:10.16182/j.issn1004731x.joss.24-0665

摘要/Abstract

摘要：

针对传统人工势场法存在目标区域不可达和易陷入局部最小值问题，提出一种改进的人工势场法。通过对斥力场函数进行优化，引入障碍物角度因子和距离因子来控制斥力大小，同时添加朝向目标点的额外斥力，解决传统算法中目标区域不可达问题；当机器人陷入局部最小值时，通过引入转向障碍物和转向因子对机器人准确施加逃逸力，有效解决了机器人易陷入局部最小值的问题。仿真实验表明：在常规环境和复杂环境中，该改进算法均能克服上述问题并规划出一条平滑路径，相较于其他算法规划的路径质量更优、规划时间更短。

关键词: 路径规划, 人工势场法, 移动机器人, 局部最小值, 逃逸力

Abstract:

In view of the problems of unreachable target areas and easy local minima in traditional artificial potential field methods, an improved artificial potential field method was proposed. The improved algorithm optimized the repulsive field function by introducing obstacle angle factors and distance factors to control the repulsive force magnitude. At the same time, an additional repulsive force towards the target point was added to solve the problem of unreachable target areas in traditional algorithms. When the robot fell into a local minimum, by introducing turning towards obstacles and turning factors to accurately apply escape forces to the robot, the problem of robots easily falling into local minima was effectively solved. Simulation experiments show that in both conventional and complex environments, the improved algorithm can overcome the above problems and plan a smooth path. Compared with other algorithms, the path quality of the improved algorithm is better, and the planning time is shorter.

Key words: path planning, artificial potential field method, mobile robot, local minima, escape force

中图分类号:

TP242

张弛,魏巍 . 基于改进人工势场法的移动机器人路径规划[J]. 系统仿真学报, 2025, 37(11): 2918-2926.

Zhang Chi,Wei Wei . Path Planning for Mobile Robots Based on Improved Artificial Potential Field Algorithm[J]. Journal of System Simulation, 2025, 37(11): 2918-2926.

图/表 17

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参数数据

参数名称	数量/大小
引力增益系数 $k a t t$	1
斥力增益系数 $k r e p$	10
障碍物影响距离 $ρ o$	3
步长	0.01
障碍物数量	9

表1

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表2

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参考文献 17

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算法	路径长度/m	迭代次数	时间/s
传统人工势场法	—	3 001	0.207
文献[15]改进算法	9.57	1 106	0.175
本文改进算法	9.03	904	0.143