{"title":"利用自由构型空间的自适应毛刺进行路径规划","authors":"B. Lacevic, Dinko Osmankovic, Adnan Ademovic","doi":"10.1109/ICAT.2017.8171616","DOIUrl":null,"url":null,"abstract":"This paper presents an adaptive version of the path planning algorithm based on the recently proposed structure called bur of free configuration space. The original planning algorithm — rapidly exploring bur tree (RBT) is based on the multi-directional extension of tree nodes for efficient exploration of free configuration space. A suitable number of directions for extension (extension degree) was empirically determined and has been kept fixed during the algorithm run. This paper investigates the possibility to adapt the extension degree during the algorithm execution in order to further boost the efficiency of the path planner in terms of number of iterations and runtime. Validation study demonstrates that the proposed adaptive version of RBT algorithm (aRBT) outperforms the original algorithm.","PeriodicalId":112404,"journal":{"name":"2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Path planning using adaptive burs of free configuration space\",\"authors\":\"B. Lacevic, Dinko Osmankovic, Adnan Ademovic\",\"doi\":\"10.1109/ICAT.2017.8171616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an adaptive version of the path planning algorithm based on the recently proposed structure called bur of free configuration space. The original planning algorithm — rapidly exploring bur tree (RBT) is based on the multi-directional extension of tree nodes for efficient exploration of free configuration space. A suitable number of directions for extension (extension degree) was empirically determined and has been kept fixed during the algorithm run. This paper investigates the possibility to adapt the extension degree during the algorithm execution in order to further boost the efficiency of the path planner in terms of number of iterations and runtime. Validation study demonstrates that the proposed adaptive version of RBT algorithm (aRBT) outperforms the original algorithm.\",\"PeriodicalId\":112404,\"journal\":{\"name\":\"2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT)\",\"volume\":\"180 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAT.2017.8171616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAT.2017.8171616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Path planning using adaptive burs of free configuration space
This paper presents an adaptive version of the path planning algorithm based on the recently proposed structure called bur of free configuration space. The original planning algorithm — rapidly exploring bur tree (RBT) is based on the multi-directional extension of tree nodes for efficient exploration of free configuration space. A suitable number of directions for extension (extension degree) was empirically determined and has been kept fixed during the algorithm run. This paper investigates the possibility to adapt the extension degree during the algorithm execution in order to further boost the efficiency of the path planner in terms of number of iterations and runtime. Validation study demonstrates that the proposed adaptive version of RBT algorithm (aRBT) outperforms the original algorithm.