{"title":"A New Approach to Increase Performance of Rapidly-Exploring Random Trees (RRT) in Mobile Robotics","authors":"E. Ege, A. Saranli","doi":"10.1109/SIU.2006.1659792","DOIUrl":null,"url":null,"abstract":"Significant recent advances have been achieved in the mobile robotics area partly due to technological advances in low power computational resources, new power storage technologies and biologically inspired principles in robotics. Despite these advances, primary problems of robotics are still open for contribution. One of these problems is path planning/finding for mobile robots. There are a number of different methods proposed for path planning. One of the recent alternatives is the rapidly-exploring random trees (RRT). In this study, we propose a new approach to the nearest neighbor finding section of the method which promises to increase the speed performance of the algorithm","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"341 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 14th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2006.1659792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Significant recent advances have been achieved in the mobile robotics area partly due to technological advances in low power computational resources, new power storage technologies and biologically inspired principles in robotics. Despite these advances, primary problems of robotics are still open for contribution. One of these problems is path planning/finding for mobile robots. There are a number of different methods proposed for path planning. One of the recent alternatives is the rapidly-exploring random trees (RRT). In this study, we propose a new approach to the nearest neighbor finding section of the method which promises to increase the speed performance of the algorithm
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