Vision-based Monte-Carlo localization for humanoid soccer robots

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dc.contributor.authorALMEIDA, A. C.
dc.contributor.authorCOSTA, A. H. R.
dc.contributor.authorReinaldo Bianchi
dc.contributor.authorOrcidhttps://orcid.org/0000-0001-9097-827X
dc.date.accessioned2022-01-12T21:57:43Z
dc.date.available2022-01-12T21:57:43Z
dc.date.issued2017-11-17
dc.description.abstract© 2017 IEEE.In order to solve the self-localization problem, the Monte-Carlo Localization is proposed as a technique which is able to solve any localization problem. However, the implemented algorithm needs to be adapted to the robot and domain. Thus, this work presents a novel implementation for humanoid robots whose main sensory input is a camera, to be used in the domain of RoboCup Humanoid Soccer League. The paper proposes motion and observation models designed for the domain, and a method to determine the quantity of particles needed to represent the probability distribution. Finally, the proposals are validated by simulated experiments.
dc.description.firstpage1
dc.description.lastpage6
dc.description.volume2017-December
dc.identifier.citationALMEIDA, A. C.; COSTA, A. H. R.; BIANCHI, R. Vision-based Monte-Carlo localization for humanoid soccer robots. Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017, p. 1-6, Nov. 2017.
dc.identifier.doi10.1109/SBR-LARS-R.2017.8215310
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/3813
dc.relation.ispartofProceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017
dc.rightsAcesso Restrito
dc.titleVision-based Monte-Carlo localization for humanoid soccer robots
dc.typeArtigo de evento
fei.scopus.citations3
fei.scopus.eid2-s2.0-85048568139
fei.scopus.subjectHumanoid robot
fei.scopus.subjectHumanoid soccer robots
fei.scopus.subjectLocalization problems
fei.scopus.subjectMonte Carlo localization
fei.scopus.subjectObservation model
fei.scopus.subjectSelf localization
fei.scopus.subjectSensory input
fei.scopus.subjectSimulated experiments
fei.scopus.updated2024-12-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85048568139&origin=inward
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