Publication:
Trajectory Planning for Multi-Robot Systems: Methods and Applications

dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Sistemas Inteligenteses
dc.contributor.authorMadridano Carrasco, Ángel
dc.contributor.authorAl Kaff, Abdulla Hussein Abdulrahman
dc.contributor.authorMartín Gómez, David
dc.contributor.authorEscalera Hueso, Arturo de la
dc.contributor.funderComunidad de Madrides
dc.date.accessioned2022-06-27T09:23:45Z
dc.date.available2023-07-01T23:00:05Z
dc.date.issued2021-07-01
dc.description.abstractIn the multiple fields covered by Artificial Intelligence (AI), path planning is undoubtedly one of the issues that cover a wide range of research lines. To be able to find an optimal solution, which allows one or several vehicles to establish a safe and effective way to reach a final state from an initial state, is a challenge that continues to be studied today. The increasingly widespread use of autonomous vehicles, both aerial and ground-based, make path planning an essential aspect for incorporating these systems into an endless number of applications. Besides, in recent years, the use of Multi-Robot Systems (MRS) has spread, consisting of both Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), gaining versatility and robustness in their operation. The possibility of using heterogeneous robotic teams allows tackling, autonomously, and simultaneously, a wide range of tasks with different characteristics in the same environment. For this purpose, path planning becomes a crucial aspect and, for this reason, this work aims to offer a general vision of trajectory planning, to establish a comparison between the methods and algorithms present in the literature for the resolution of this problem within MRS, and finally, to show the applicability of these methods in different areas, together with the importance of these methods for achieving autonomous and safe navigation of different types of vehicles.en
dc.description.sponsorshipThis work was supported also by the Comunidad de Madrid Government through the Industrial Doctorates Grants (GRANT IND2017/TIC-7834).en
dc.description.statusPublicadoes
dc.format.extent14
dc.identifier.bibliographicCitationExpert Systems with Applications, (2021), v. 173, 114660.en
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2021.114660
dc.identifier.issn0957-4174
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue1, 114660
dc.identifier.publicationlastpage14
dc.identifier.publicationtitleEXPERT SYSTEMS WITH APPLICATIONSen
dc.identifier.publicationvolume173
dc.identifier.urihttps://hdl.handle.net/10016/35292
dc.identifier.uxxiAR/0000028912
dc.language.isoengen
dc.publisherElsevieren
dc.relation.projectIDComunidad de Madrid. IND2017/TIC-7834es
dc.rights© 2021 Elsevier Ltd. All rights reserved.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaInformáticaes
dc.subject.otherAutonomous vehiclesen
dc.subject.otherPath planningen
dc.subject.otherMulti-robot systemsen
dc.subject.otherUAVsen
dc.subject.otherUGVsen
dc.titleTrajectory Planning for Multi-Robot Systems: Methods and Applicationsen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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