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Mobile Robot Navigation Based on Embedded Computer Vision

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dc.contributor.authorMarroquín, Alberto
dc.contributor.authorGarcía, Gonzalo
dc.contributor.authorFábregas Acosta, Ernesto
dc.contributor.authorAranda Escolástico, Ernesto
dc.contributor.authorFarias, Gonzalo
dc.contributor.orcidhttps://orcid.org/0000-0001-6354-0520
dc.contributor.orcidhttps://orcid.org/0000-0001-9968-960X
dc.contributor.orcidhttps://orcid.org/0000-0003-2186-4126
dc.date.accessioned2024-10-07T10:30:14Z
dc.date.available2024-10-07T10:30:14Z
dc.date.issued2023
dc.descriptionThe registered version of this article, first published in “Mathematics 11, no. 11", is available online at the publisher's website: MDPI, https://doi.org/10.3390/math11112561 La versión registrada de este artículo, publicado por primera vez en “Mathematics 11, no. 11", está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/math11112561
dc.description.abstractThe current computational advance allows the development of technological solutions using tools, such as mobile robots and programmable electronic systems. We present a design that integrates the Khepera IV mobile robot with an NVIDIA Jetson Xavier NX board. This system executes an algorithm for navigation control based on computer vision and the use of a model for object detection. Among the functionalities that this integration adds to the Khepera IV in generating guided driving are trajectory tracking for safe navigation and the detection of traffic signs for decision-making. We built a robotic platform to test the system in real time. We also compared it with a digital model of the Khepera IV in the CoppeliaSim simulator. The navigation control results show significant improvements over previous works. This is evident in both the maximum navigation speed and the hit rate of the traffic sign detection system. We also analyzed the navigation control, which achieved an average success rate of 93%. The architecture allows testing new control techniques or algorithms based on Python, facilitating future improvements.en
dc.description.versionversión final
dc.identifier.citationMarroquín, Alberto, Gonzalo Garcia, Ernesto Fabregas, Ernesto Aranda-Escolástico, and Gonzalo Farias. 2023. "Mobile Robot Navigation Based on Embedded Computer Vision" Mathematics 11, no. 11: 2561. https://doi.org/10.3390/math11112561
dc.identifier.doihttps://doi.org/10.3390/math11112561
dc.identifier.issn2227-7390
dc.identifier.urihttps://hdl.handle.net/20.500.14468/23936
dc.journal.issue11
dc.journal.titleMathematics 11(11):1-17
dc.journal.volume11
dc.language.isoen
dc.page.final17
dc.page.initial1
dc.publisherMDPI
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentIngeniería de Software y Sistemas Informáticos
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.es
dc.subject33 Ciencias Tecnológicas
dc.subject.keywordsMobile Roboten
dc.subject.keywordsComputer Visionen
dc.subject.keywordsObject Detectoren
dc.subject.keywordsTraffic Signsen
dc.subject.keywordsKheperaen
dc.subject.keywordsJetson Xavier 13 NXen
dc.titleMobile Robot Navigation Based on Embedded Computer Visionen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublication04fadb3a-7297-4110-ae10-c2397dd66eb4
relation.isAuthorOfPublication19c0c538-4e7e-4de5-afd9-6ff1a8bbf88e
relation.isAuthorOfPublication.latestForDiscovery04fadb3a-7297-4110-ae10-c2397dd66eb4
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