{"title":"Visual collision avoidance by segmentation","authors":"I. Horswill","doi":"10.1109/IROS.1994.407486","DOIUrl":null,"url":null,"abstract":"Visual collision avoidance involves two difficult subproblems: obstacle recognition and depth measurement. We present a class of algorithms that use particularly simple methods for each subproblem and derive a set of sufficient conditions for their proper functioning based on a set of idealizations. We then discuss and compare two different implementations of the approach on mobile robots and discuss their performance. Finally, we experimentally validate the idealizations.<<ETX>>","PeriodicalId":437805,"journal":{"name":"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"59","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1994.407486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 59
Abstract
Visual collision avoidance involves two difficult subproblems: obstacle recognition and depth measurement. We present a class of algorithms that use particularly simple methods for each subproblem and derive a set of sufficient conditions for their proper functioning based on a set of idealizations. We then discuss and compare two different implementations of the approach on mobile robots and discuss their performance. Finally, we experimentally validate the idealizations.<>
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