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dc.creatorMedina Sánchez, Carloses
dc.creatorJanzon, Simones
dc.creatorZella, Matteoes
dc.creatorCapitán Fernández, Jesúses
dc.creatorMarrón, P. J.es
dc.date.accessioned2024-02-14T10:07:22Z
dc.date.available2024-02-14T10:07:22Z
dc.date.issued2023-12
dc.identifier.citationMedina Sánchez, C., Janzon, S., Zella, M., Capitán Fernández, J. y Marrón, P.J. (2023). Human-Aware Navigation in Crowded Environments Using Adaptive Proxemic Area and Group Detection. En IEEE International Conference on Intelligent Robots and Systems (6741-6748), Detroit, MI, USA: Institute of Electrical and Electronics Engineers.
dc.identifier.isbn978-1-6654-9190-7es
dc.identifier.isbn978-1-6654-9191-4es
dc.identifier.issn2153-0866es
dc.identifier.issn2153-0858es
dc.identifier.urihttps://hdl.handle.net/11441/155219
dc.description.abstractNavigation is an essential task for social robots. However, certain rules must be followed to allow them to move without causing distraction or discomfort to people. Considering that the context surrounding robots and persons affects the expected behavior, this work defines a social area around a person that adapts to the real situation. In addition, the social context of a person is extended to identify groups of people, which the robot should take into account while navigating. With this understanding of the surrounding of the robot together with the ability to predict the trajectory of individuals as well as groups, the proposed solution not only effectively addresses collision avoidance while promoting socially acceptable behavior but also outperforms the majority of recent works in terms of accuracy. Furthermore, a dedicated policy is introduced to react to social navigation conflicts. The evaluation performed in a simulated environment shows that the computation of our proposed solution is at least 8 times faster than the best state-of-the-art approach while preserving comparable social conduct. Also, the results of realistic experiments performed using Gazebo and a real robot are reported.es
dc.formatapplication/pdfes
dc.format.extent8 p.es
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineerses
dc.relation.ispartofIEEE International Conference on Intelligent Robots and Systems (2023), pp. 6741-6748.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCostses
dc.subjectNavigationes
dc.subjectSocial robotses
dc.subjectTrajectoryes
dc.subjectBehavioral scienceses
dc.subjectResource managementes
dc.subjectCollision avoidancees
dc.titleHuman-Aware Navigation in Crowded Environments Using Adaptive Proxemic Area and Group Detectiones
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.type.versioninfo:eu-repo/semantics/acceptedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/10342385es
dc.identifier.doi10.1109/IROS55552.2023.10342385es
dc.contributor.groupUniversidad de Sevilla. TEP995: Multi-robot and Control Systemses
idus.validador.notaPostprint. Acepted versiones
dc.publication.initialPage6741es
dc.publication.endPage6748es
dc.eventtitleIEEE International Conference on Intelligent Robots and Systemses
dc.eventinstitutionDetroit, MI, USAes

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