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Cited 9 time in webofscience Cited 13 time in scopus
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dc.contributor.authorJung-Suk Lee-
dc.contributor.authorSang Yep Nam-
dc.contributor.authorChung, WK-
dc.date.accessioned2016-03-31T09:26:46Z-
dc.date.available2016-03-31T09:26:46Z-
dc.date.created2012-04-30-
dc.date.issued2011-01-
dc.identifier.issn0169-1864-
dc.identifier.other2011-OAK-0000024037-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/17195-
dc.description.abstractWe propose a robust simultaneous localization and mapping (SLAM) with a Rao-Blackwellized particle filter (RBPF) algorithm for mobile robots using sonar sensors in non-static environments. The algorithm consists of three parts: sampling from multiple ancestor sets, estimating intermediate paths for map updates and eliminating spurious landmarks using negative information from sonar sensors. The proposed sampling method, in which particles are sampled from multiple ancestor sets, increases the robustness of the estimation of the robot's pose, even if environmental changes corrupt observations. This step increases the probability of some particles being sampled from correct ancestor sets that are updated by observations reflected from stationary objects. When particles are sampled from several time steps earlier, however, observations at intermediate time steps cannot be used to update the map because of the lack of information about the intermediate path. To update the map with all sensor information, the intermediate path is estimated after particles are sampled from ancestor sets. Finally, spurious landmarks still exist on the map representing objects that were eliminated or that were extracted by error in cluttered areas. These are eliminated in the final step using negative information from the sonar sensors. The performance of the proposed SLAM algorithm was verified through simulations and experiments in various non-static environments. (C) Koninklijke Brill NV, Leiden, 2011-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherVSP BV-
dc.relation.isPartOfADVANCED ROBOTICS-
dc.subjectRBPF-SLAM-
dc.subjectnon-static environment-
dc.subjectmobile robot-
dc.subjectparticle filtering-
dc.subjectLOCALIZATION-
dc.titleRobust RBPF-SLAM for Indoor Mobile Robots Using Sonar Sensors in Non-Static Environments-
dc.typeArticle-
dc.contributor.college기계공학과-
dc.identifier.doi10.1163/016918611X574696-
dc.author.googleLee, JS-
dc.author.googleNam, SY-
dc.author.googleChung, WK-
dc.relation.volume25-
dc.relation.issue9-
dc.relation.startpage1227-
dc.relation.lastpage1248-
dc.contributor.id10077435-
dc.relation.journalADVANCED ROBOTICS-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.relation.sciSCIE-
dc.collections.nameJournal Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationADVANCED ROBOTICS, v.25, no.9, pp.1227 - 1248-
dc.identifier.wosid000292770600007-
dc.date.tcdate2019-01-01-
dc.citation.endPage1248-
dc.citation.number9-
dc.citation.startPage1227-
dc.citation.titleADVANCED ROBOTICS-
dc.citation.volume25-
dc.contributor.affiliatedAuthorChung, WK-
dc.identifier.scopusid2-s2.0-79959560469-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc2-
dc.description.scptc2*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordAuthorRBPF-SLAM-
dc.subject.keywordAuthornon-static environment-
dc.subject.keywordAuthormobile robot-
dc.subject.keywordAuthorparticle filtering-
dc.relation.journalWebOfScienceCategoryRobotics-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaRobotics-

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정완균CHUNG, WAN KYUN
Dept of Mechanical Enginrg
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