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.