Global path guided vehicle obstacle avoidance path planning with artificial potential field method

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS IET Cybersystems and Robotics Pub Date : 2023-02-16 DOI:10.1049/csy2.12082
Yangde Chen, Peiliang Wang, Zichen Lin, Chenhao Sun
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引用次数: 1

Abstract

An artificial potential field method based on global path guidance (G-APF) is proposed for target unreachability and local minima problems of the conventional artificial potential field (APF) method in complex environments with dynamic obstacles. First, for the target unreachability problem, the global path attraction is added to the APF; second, an obstacle detection optimisation method is proposed and the optimal virtual target point is selected by setting the evaluation function to improve the local minima problem; finally, based on the obstacle detection optimisation method, the gravitational and repulsive processes are improved so that the path can pass through the narrow channel smoothly and remain collision-free. Experiments show that the method optimises 40.8% of the total path corners, reduces 81.8% of the number of path oscillations, and shortens 4.3% of the path length in Map 1. It can be applied to the vehicle obstacle avoidance path planning problem in complex environments with dynamic obstacles.

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基于人工势场法的全局路径引导车辆避障路径规划
针对传统人工势场法在具有动态障碍物的复杂环境中存在的目标不可达性和局部极小问题,提出了一种基于全局路径制导的人工势场法。首先,针对目标不可达性问题,在APF中加入全局路径吸引;其次,提出了一种障碍物检测优化方法,通过设置评价函数选择最优虚拟目标点,改进了局部极小问题;最后,在障碍物检测优化方法的基础上,对引力和斥力过程进行改进,使路径能够顺利通过窄通道并保持无碰撞。实验表明,该方法优化了40.8%的路径角,减少了81.8%的路径振荡次数,缩短了4.3%的路径长度。该方法可应用于具有动态障碍物的复杂环境下的车辆避障路径规划问题。
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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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