基于三角不等式的改进RRT-Connect算法用于机器人路径规划

Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning.

作者信息

Kang Jin-Gu, Lim Dong-Woo, Choi Yong-Sik, Jang Woo-Jin, Jung Jin-Woo

机构信息

Department of Computer Science and Engineering, Dongguk University, Seoul 04620, Korea.

Department of Artificial Intelligence, Dongguk University, Seoul 04620, Korea.

出版信息

Sensors (Basel). 2021 Jan 6;21(2):333. doi: 10.3390/s21020333.

DOI:10.3390/s21020333

PMID:33419005

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7825297/

Abstract

This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm's performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

摘要

本文针对快速扩展随机树（RRT）-Connect机器人路径规划算法提出了一种基于三角不等式的重布线方法，与RRT算法相比，该方法能保证规划时间，使其更接近最优解。为检验所提算法的性能，本文通过仿真在各种环境下对RRT和RRT-Connect算法进行了比较。从这些实验结果来看，所提算法在样本数量和规划时间相近的情况下，与RRT算法相比，规划时间更快，路径长度更短；与RRT-Connect算法相比，路径长度更短。