APF-RRT*: An Efficient Sampling-Based Path Planning Method with the Guidance of Artificial Potential Field

被引:7
|
作者
Ma, Benshan [1 ]
Wei, Chao [1 ]
Huang, Qing [1 ]
Hu, Jibin [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Beijing, Peoples R China
来源
2023 9TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND ROBOTICS ENGINEERING, ICMRE | 2023年
关键词
path planning; sampling-based algorithm; RRT*; artificial potential field; QUICK;
D O I
10.1109/ICMRE56789.2023.10106516
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Path planning is a decisive module of mobile robots and its time efficiency significantly affects the safety of the robots. Sampling-based methods have achieved great success in the robotic path planning domain. However, poor time efficiency is still a serious limitation when they are applied to a crowded environment. In this paper, we combine the RRT* algorithm and artificial potential field(APF) technic and propose an efficient sampling-based path planning method named APF-RRT*. Utilizing the prior knowledge of the mission and the environment, we construct APFs for the start point, the goal point, the reference path, and the obstacles. Then we modify the random sampling step of the RRT* algorithm. With the guidance of APF, the random sample points are closer to the optimal path, and useless sample points greatly decrease. Results show that the proposed APF-RRT* outperforms state-of-the-art sampling-based methods in convergence rate, sampling effectiveness, and time efficiency.
引用
收藏
页码:207 / 213
页数:7
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