基于融合改进双向RRT与人工势场法路径规划

doi:10.16039/j.cnki.cn22-1249.2023.07.006

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摘要

由于快速扩展随机树（RRT）算法在路径规划中存在速度慢，计算量大和效率低等问题，提出一种双向快速扩展随机树（RRT）算法与人工势场法（APF）相结合的路径规划。首先，通过利用人工势场法（APF）进行局部路径规划，提供运动路径。其次，通过使用改进的快速扩展随机树算法选择临时目标点，用以解决路径规划时陷入最小值的问题，将人工势场法（APF）引入双向RRT算法中。将局部路径规划与全局路径规划相结合，缩短运行时间和路径长度，基于仿真实验表明，该方法在运行时间、路径长度和迭代次数等方面都得到显著提高。

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	钱程
	刘兴德
	陈大光

关键词: RRT算法 APF算法路径规划

Abstract:

Due to the slow speed of the Rapid Expansion Random Tree (RRT) algorithm in path planning，computationally intensive and inefficient,In this paper, a path planning based on the combination of Two-Way Rapidly Extended Random Tree (RRT) algorithm and Artificial Potential Field Method (APF) was proposed.Firstly, the local path planning is carried out by using the artificial potential field method (APF) to provide the motion path.Secondly, by using the improved fast-expanding random tree algorithm to select the temporary target points,In order to solve the problem of falling into the minimum value in path planning, the artificial potential field method (APF) was introduced into the bidirectional RRT algorithm.Combine local path planning with global path planning to reduce run time and path length,Based on simulation experiments, the proposed method is significantly improved in terms of running time, path length and iteration times.

Key words: RRT algorithm APF algorithm path planning

出版日期: 2023-07-25 发布日期: 2023-07-25 整期出版日期: 2023-07-25

ZTFLH:

TP242

引用本文:

钱程 , 刘兴德 , 陈大光. 基于融合改进双向RRT与人工势场法路径规划 [J]. 吉林化工学院学报, 2023, 40(7): 30-33.
QIAN Cheng, LIU Xingde, CHENG Daguang. Improved APF-RRT Path Planning based on Fusion . Journal of Jilin Institute of Chemical Technology, 2023, 40(7): 30-33.

链接本文:

http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.07.006 或 http://xuebao.jlict.edu.cn/CN/Y2023/V40/I7/30

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