A qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration

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dc.contributor.authorPEREIRA, V. F.
dc.contributor.authorCOZMAN, F. G.
dc.contributor.authorPaulo Santos
dc.contributor.authorMARTINS, M. F.
dc.contributor.authorOrcidhttps://orcid.org/0000-0001-8484-0354
dc.date.accessioned2022-01-12T22:01:45Z
dc.date.available2022-01-12T22:01:45Z
dc.date.issued2013-10-20
dc.description.abstractTypically, the spatial features of a robot's environment are specified using metric coordinates, and well-known mobile robot localisation techniques are used to track the exact robot position. In this paper, a qualitative-probabilistic approach is proposed to address the problem of mobile robot localisation. This approach combines a recently proposed logic theory called Perceptual Qualitative Reasoning about Shadows (PQRS) with a Bayesian filter. The approach herein proposed was systematically evaluated through experiments using a mobile robot in a real environment, where the sequential prediction and measurement steps of the Bayesian filter are used to both self-localisation and self-calibration of the robot's vision system from the observation of object's and their shadows. The results demonstrate that the qualitative-probabilistic approach effectively improves the accuracy of robot localisation, keeping the vision system well calibrated so that shadows can be properly detected. © 2013 IEEE.
dc.description.firstpage157
dc.description.lastpage162
dc.identifier.citationPEREIRA, V. F.; COZMAN, F. G.; SANTOS, P.; MARTINS, M. F. A qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration. Proceedings - 2013 Brazilian Conference on Intelligent Systems, BRACIS 2013, p157-162, Oct. 2013.
dc.identifier.doi10.1109/BRACIS.2013.34
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/4089
dc.relation.ispartofProceedings - 2013 Brazilian Conference on Intelligent Systems, BRACIS 2013
dc.rightsAcesso Restrito
dc.subject.otherlanguageBayesian Filtering
dc.subject.otherlanguageMobile Robot
dc.subject.otherlanguageQualitative Spatial Reasoning
dc.subject.otherlanguageSelf-localisation
dc.titleA qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration
dc.typeArtigo de evento
fei.scopus.citations6
fei.scopus.eid2-s2.0-84894169595
fei.scopus.subjectAutonomous Mobile Robot
fei.scopus.subjectBayesian filtering
fei.scopus.subjectQualitative reasoning
fei.scopus.subjectQualitative spatial reasoning
fei.scopus.subjectRobot localisation
fei.scopus.subjectSelf-localisation
fei.scopus.subjectSequential prediction
fei.scopus.subjectVision calibrations
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84894169595&origin=inward
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