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Experimental Evaluation of Data Fusion Techniques and Adaptive Control for Mobile Robot Localization

2025Comunicação em conferência Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorAraújo Neto, Wolmar
dc.contributor.authorVilla, Daniel Khede Dourado
dc.contributor.authorSarcinelli-Filho, Mário
dc.contributor.authorSantos, Murillo Ferreira Dos
dc.contributor.authorLima, José
dc.contributor.authorPereira, Ana I.
dc.contributor.authorMorais, Maurício Herche Fófano De
dc.contributor.authorMercorelli, Paolo
dc.date.accessioned2026-03-16T14:35:44Z
dc.date.available2026-03-16T14:35:44Z
dc.date.issued2025
dc.date.updated2026-03-11T19:45:24Z
dc.description.abstractThis study presents an approach to improving the localization of mobile robots in a controlled test environment through sensor fusion. Currently, the position of the ground robot (Unmanned Ground Vehicle (UGV) P3DX) can be estimated using an optimization algorithm or another technique based on a previously known map. In contrast, the aerial robot (Unmanned Aerial Vehicle (UAV) Bebop Parrot 2) can determine its relative position by detecting a marker on the ground robot using the Robot Operating System (ROS) WhyCon package. However, ambiguities or disturbances may compromise the accuracy of the robots' localization. To mitigate these limitations, Ultra-WideBand (UWB) sensors were incorporated into the system, enabling a more robust data fusion by integrating information from multiple sensors. Additionally, a filter was applied to reduce the impact of high-frequency noise on position estimation. Accurate localization test data were used to construct a simulated scenario and analyze the performance of the proposed approach. The simulation results demonstrate that sensor fusion, combined with noise filtering, significantly improves localization accuracy, making the approach promising for applications in mobile robot navigation.eng
dc.description.sponsorshipThe authors gratefully acknowledge the support of UFES, CEFET-MG, and IPB for their collaboration.
dc.description.versionN/A
dc.identifier.citationAraújo Neto, Wolmar; Villa, Daniel Khede Dourado; Sarcinelli-Filho, Mário; Santos, Murillo Ferreira Dos; Lima, José; Pereira, Ana I.; Morais, Maurício Herche Fófano De; Mercorelli, Paolo (2025). Experimental Evaluation of Data Fusion Techniques and Adaptive Control for Mobile Robot Localization. In 26th International Carpathian Control Conference, ICCC 2025. Stary Smokovec:IEEE. p. 1-6. ISBN 979-833150127-3
dc.identifier.doi10.1109/iccc65605.2025.11022810en_US
dc.identifier.eid2-s2.0-105008967312en_US
dc.identifier.isbn979-833150127-3
dc.identifier.urihttp://hdl.handle.net/10198/36084
dc.language.isoeng
dc.peerreviewedyes
dc.publisherInstitute of Electrical and Electronics Engineers
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/
dc.subjectPosition estimation
dc.subjectData fusion
dc.subjectAdaptive control
dc.subjectUAV
dc.subjectUGV
dc.titleExperimental Evaluation of Data Fusion Techniques and Adaptive Control for Mobile Robot Localizationeng
dc.typeconference paperen_US
dspace.entity.typePublication
oaire.citation.conferencePlaceEslováquiaen_US
oaire.citation.endPage6
oaire.citation.startPage1
oaire.citation.title26th International Carpathian Control Conference, ICCC 2025
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLima
person.familyNamePereira
person.givenNameJosé
person.givenNameAna I.
person.identifierR-000-8GD
person.identifier.ciencia-id6016-C902-86A9
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0000-0001-7902-1207
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridL-3370-2014
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id55851941311
person.identifier.scopus-author-id15071961600
rcaap.cv.cienciaid1517-A459-54E4 | Maurício Herche Fófano de Morais
rcaap.rightsopenAccessen_US
relation.isAuthorOfPublicationd88c2b2a-efc2-48ef-b1fd-1145475e0055
relation.isAuthorOfPublicatione9981d62-2a2b-4fef-b75e-c2a14b0e7846
relation.isAuthorOfPublication.latestForDiscoveryd88c2b2a-efc2-48ef-b1fd-1145475e0055

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