@inproceedings{43d563e08fbb45e3a7f074e49b36af91,
title = "Path Planning for Lunar Rover Based on Bi-RRT Algorithm",
abstract = "A new method based on the Bi-RRT (Bidirectional Rapidly exploring Random Tree) algorithm, APF (Artificial Potential Field) algorithm, and DOM (Digital Orthophoto Map) is presented in this paper to solve the lunar rover path planning problem. First, we use DOM to build an occupancy grid map through an image processing algorithm. Then we build a repulsive potential field based on the obstacle and an attractive potential field based on the target. We then designed an improved Bi-RRT algorithm based on a novel potential field guidance growth method and a goal bias sampling method. Finally, a simulation was carried out on the lunar DOM to verify the efficiency and safety of the proposed Bi-RRT-APF algorithm. The results show that the searching efficiency of the Bi-RRT-APF algorithm is increased by twice compared with the Bi-RRT algorithm and is increased by four times compared with the RRT-APF algorithm. The safe coefficient of the Bi-RRT-APF algorithm is increased by 42.7\% compared with the Bi-RRT algorithm.",
keywords = "APF, Bi-RRT, DOM, Lunar Rover, Path Planning",
author = "Yiming Wang and Qiufan Yuan and Yanning Guo and Weidi Han",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9549340",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4211--4216",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "美国",
}