{"title":"A vision based algorithm for active robot localization","authors":"E. Frontoni, P. Zingaretti","doi":"10.1109/CIRA.2005.1554301","DOIUrl":null,"url":null,"abstract":"This paper describes a method to localize a mobile robot in a structured indoor environment from visual information provided by omnidirectional images. In particular, an approximate algorithm for active robot localization in partially observable environments based on a POMDP model is introduced. Results from many different tests are presented to prove the setting of algorithm parameters. They show that a localization accuracy of less than 25 cm can be achieved even with a partial knowledge of the environment. Besides, the proposed approximated algorithm reduces the computational cost without degrading results.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2005.1554301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
This paper describes a method to localize a mobile robot in a structured indoor environment from visual information provided by omnidirectional images. In particular, an approximate algorithm for active robot localization in partially observable environments based on a POMDP model is introduced. Results from many different tests are presented to prove the setting of algorithm parameters. They show that a localization accuracy of less than 25 cm can be achieved even with a partial knowledge of the environment. Besides, the proposed approximated algorithm reduces the computational cost without degrading results.