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Dual UWB Anchors-Based Target Tracking Strategy for an Omnidirectional Mobile Robot

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dc.contributor.authorBao, L.-
dc.contributor.authorLi, K.-
dc.contributor.authorDong, W.-
dc.contributor.authorLi, W.-
dc.contributor.authorShin, K.-
dc.contributor.authorHan, C.-
dc.contributor.authorKim, W.-
dc.date.accessioned2025-06-19T01:30:23Z-
dc.date.available2025-06-19T01:30:23Z-
dc.date.issued2024-12-
dc.identifier.issn1598-7833-
dc.identifier.issn2642-3901-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125656-
dc.description.abstractTarget tracking mobile robots still face challenges in terms of localization accuracy and tracking performance. This study presents a novel target tracking strategy for an omnidirectional mobile robot by using dual ultra-wideband (UWB) anchors. The proposed target tracking strategy integrates these sensors with a Mecanum wheeled mobile platform, optimizing motion control and target tracking. Based on the developed dual UWB anchors' geometric localization model, the horizontal relative distance and orientation between the target and the robot were estimated. In tracking scenarios, the robot demonstrates advanced adaptability: While the target is at close-range, the robot rotates in place for orientation tracking to directly face the target, and the designed tracking algorithm allows the robot to dynamically adjust its rotation speed, resulting in smooth tracking movements. While the target is at longer-range, the robot dynamically modifies its tracking speed and orientation according to relative positional data, to ensure effective and continuous target following. Through experimental validation, the lateral error during target tracking is reduced, the tracking accuracy is improved by 50% compared to existing related studies, and the tracking performance is smoother. © 2024 ICROS.-
dc.format.extent6-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE Computer Society-
dc.titleDual UWB Anchors-Based Target Tracking Strategy for an Omnidirectional Mobile Robot-
dc.typeArticle-
dc.identifier.doi10.23919/ICCAS63016.2024.10773192-
dc.identifier.scopusid2-s2.0-85214402604-
dc.identifier.wosid001432930500146-
dc.identifier.bibliographicCitationInternational Conference on Control, Automation and Systems, pp 916 - 921-
dc.citation.titleInternational Conference on Control, Automation and Systems-
dc.citation.startPage916-
dc.citation.endPage921-
dc.type.docTypeConference Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaRobotics-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryRobotics-
dc.subject.keywordAuthorLocalization-
dc.subject.keywordAuthorMobile Robot-
dc.subject.keywordAuthorTarget Tracking-
dc.subject.keywordAuthorUltra-Wideband-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/10773192-
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ERICA 공학대학 (DEPARTMENT OF ROBOT ENGINEERING)
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