Panagiotis Rousseas, Charalampos P. Bechlioulis, Kostas Kyriakopoulos
{"title":"Reactive optimal motion planning to anywhere in the presence of moving obstacles","authors":"Panagiotis Rousseas, Charalampos P. Bechlioulis, Kostas Kyriakopoulos","doi":"10.1177/02783649241245729","DOIUrl":null,"url":null,"abstract":"In this paper, a novel optimal motion planning framework that enables navigating optimally from any initial, to any final position within confined workspaces with convex, moving obstacles is presented. Our method outputs a smooth velocity vector field, which is then employed as a reference controller in order to sub-optimally avoid moving obstacles. The proposed approach leverages and extends desirable properties of reactive methods in order to provide a provably convergent and safe solution. Our algorithm is evaluated with both static and moving obstacles in synthetic environments and is compared against a variety of existing methods. The efficacy and applicability of the proposed scheme is finally validated in a high-fidelity simulation environment.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"30 21","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Journal of Robotics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/02783649241245729","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
In this paper, a novel optimal motion planning framework that enables navigating optimally from any initial, to any final position within confined workspaces with convex, moving obstacles is presented. Our method outputs a smooth velocity vector field, which is then employed as a reference controller in order to sub-optimally avoid moving obstacles. The proposed approach leverages and extends desirable properties of reactive methods in order to provide a provably convergent and safe solution. Our algorithm is evaluated with both static and moving obstacles in synthetic environments and is compared against a variety of existing methods. The efficacy and applicability of the proposed scheme is finally validated in a high-fidelity simulation environment.