{"title":"Mobile Robot Path Planning Algorithm Based on Rapidly-Exploring Random Tree","authors":"Yajie Wang, Yuan Huang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00117","DOIUrl":null,"url":null,"abstract":"A path planning algorithm is proposed for the problems of high node randomness and repeatability using the Rapidly-exploring Random Tree (RRT) algorithm in the path planning. Firstly, the method of region division centered on newly generated nodes is proposed to reduce randomness, the generation rules of temporary target nodes are guided to reduce repetitiveness, then improve the efficiency of path planning through adaptive step size strategy, smooth the planned path to improve the length of the path in the end. Simulation results show that the improved RRT algorithm can effectively plan the path for mobile robots.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A path planning algorithm is proposed for the problems of high node randomness and repeatability using the Rapidly-exploring Random Tree (RRT) algorithm in the path planning. Firstly, the method of region division centered on newly generated nodes is proposed to reduce randomness, the generation rules of temporary target nodes are guided to reduce repetitiveness, then improve the efficiency of path planning through adaptive step size strategy, smooth the planned path to improve the length of the path in the end. Simulation results show that the improved RRT algorithm can effectively plan the path for mobile robots.
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