{"title":"Binary Integer Programming Model of Point Robot Path Planning","authors":"G. Habibi, E. Masehian, M. Beheshti","doi":"10.1109/IECON.2007.4460315","DOIUrl":null,"url":null,"abstract":"This paper presents a novel algorithm for path planning of point robots in 2D known environment, using binary integer programming. In this approach the problem of path planning is formulated as a binary integer programming with variables taken from Delaunay triangulation of the free configuration space. The model is then transformed into binary integer programming and solved to obtain an optimal channel made of connected triangles. The channel is then partitioned into convex fragments which are used to build safe and short paths within the channel from start to goal. The algorithm has a simple formulation, avoiding loops, and it is applicable to different workspaces with convex and concave polygonal obstacles. It can be extended to workspaces with higher dimensions as well.","PeriodicalId":199609,"journal":{"name":"IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2007.4460315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This paper presents a novel algorithm for path planning of point robots in 2D known environment, using binary integer programming. In this approach the problem of path planning is formulated as a binary integer programming with variables taken from Delaunay triangulation of the free configuration space. The model is then transformed into binary integer programming and solved to obtain an optimal channel made of connected triangles. The channel is then partitioned into convex fragments which are used to build safe and short paths within the channel from start to goal. The algorithm has a simple formulation, avoiding loops, and it is applicable to different workspaces with convex and concave polygonal obstacles. It can be extended to workspaces with higher dimensions as well.