{"title":"Range scan-based localization methods for mobile robots in complex environments","authors":"R. Mázl, Miroslav Kulich, L. Preucil","doi":"10.1109/ITSC.2001.948669","DOIUrl":null,"url":null,"abstract":"The work introduces design and comparison of different-brand methods for position localization of indoor mobile robots. Both the methods derive the robot relative position from a structure of the working environment based on measurements gathered by a TOF-based laser ranging system. The first presented method applies statistical description of the scene while the other one relies on a feature-based matching approach. Both the approaches provide method-specific behavior, which has been recognized in experiments with real data. The obtained results are compared and further improvements of the localization robustness via their combination are discussed.","PeriodicalId":173372,"journal":{"name":"ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2001.948669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The work introduces design and comparison of different-brand methods for position localization of indoor mobile robots. Both the methods derive the robot relative position from a structure of the working environment based on measurements gathered by a TOF-based laser ranging system. The first presented method applies statistical description of the scene while the other one relies on a feature-based matching approach. Both the approaches provide method-specific behavior, which has been recognized in experiments with real data. The obtained results are compared and further improvements of the localization robustness via their combination are discussed.