Improved path planning algorithm of an informed RRT algorithm in 3D space

H. Tian, S. Huang, P. F. Wang, C. Xiang, J. Cao, R. Teo
{"title":"Improved path planning algorithm of an informed RRT algorithm in 3D space","authors":"H. Tian, S. Huang, P. F. Wang, C. Xiang, J. Cao, R. Teo","doi":"10.1109/ICUAS57906.2023.10155972","DOIUrl":null,"url":null,"abstract":"The main purpose of drone flight is to find an optimal path without colliding with obstacles. The key point is to design a search algorithm. Path planning for searching a 2-dimensional (2D) map has been studied extensively and reached a mature stage. For a higher-dimensional configuration space, it is quite challenging. In this paper, a sampling based path planning method is proposed. It uses the rapidly-exploring random trees (RRT) concept. An improved guidance is proposed for reducing the search space in the present algorithm in a 3D clutter environment. Simulation is given to show the effectiveness of the proposed method.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS57906.2023.10155972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The main purpose of drone flight is to find an optimal path without colliding with obstacles. The key point is to design a search algorithm. Path planning for searching a 2-dimensional (2D) map has been studied extensively and reached a mature stage. For a higher-dimensional configuration space, it is quite challenging. In this paper, a sampling based path planning method is proposed. It uses the rapidly-exploring random trees (RRT) concept. An improved guidance is proposed for reducing the search space in the present algorithm in a 3D clutter environment. Simulation is given to show the effectiveness of the proposed method.
一种改进的三维空间知情RRT算法的路径规划算法
无人机飞行的主要目的是寻找一条不与障碍物相撞的最优路径。关键是设计一个搜索算法。二维地图搜索路径规划的研究已进入成熟阶段。对于高维构型空间,这是相当具有挑战性的。本文提出了一种基于采样的路径规划方法。它使用了快速探索随机树(RRT)的概念。在三维杂波环境下,提出了一种改进的制导方法来减小算法的搜索空间。仿真结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信