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dc.creatorBalampanis, Fotioses
dc.creatorMaza Alcañiz, Ivánes
dc.creatorOllero Baturone, Aníbales
dc.date.accessioned2017-06-26T15:34:42Z
dc.date.available2017-06-26T15:34:42Z
dc.date.issued2017-04-09
dc.identifier.citationBalampanis, F., Maza Alcañiz, I. y Ollero Baturone, A. (2017). Coastal Areas Division and Coverage with Multiple UAVs for Remote Sensing. Sensors, 17 (4), 1-25.
dc.identifier.issn1424-8220es
dc.identifier.urihttp://hdl.handle.net/11441/61521
dc.description.abstractThis paper tackles the problems of exact cell decomposition and partitioning of a coastal region for a team of heterogeneous Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the field of view or sensing radius of the sensors on-board. An initial sensor-based exact celldecompositionoftheareaaidsinthepartitioningprocess,whichisperformedintwosteps. Inthe first step, a growing regions algorithm performs an isotropic partitioning of the area based on the initial locations of the UAVs and their relative capabilities. Then, two novel algorithms are applied to compute an adjustment of this partitioning process, in order to solve deadlock situations that generate non-allocated regions and sub-areas above or below the relative capabilities of the UAVs. Finally, realistic simulations have been conducted for the evaluation of the proposed solution, and the obtained results show that these algorithms can compute valid and sound solutions in complex coastal region scenarios under different setups for the UAVses
dc.description.sponsorshipMinisterio de Economía, Industria y Competitividad DPI2014-C2-1-Res
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSensors, 17 (4), 1-25.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRemote sensorses
dc.subjectUnmanned Aerial Vehicleses
dc.subjectArea partitiones
dc.subjectCell decompositiones
dc.titleCoastal Areas Division and Coverage with Multiple UAVs for Remote Sensinges
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/DPI2014-59383-C2-1-Res
dc.relation.publisherversionhttp://dx.doi.org/10.3390/s17040808es
dc.identifier.doi10.3390/s17040808es
dc.contributor.groupUniversidad de Sevilla. TEP151: Robótica, Visión y Controles
idus.format.extent25 p.es
dc.journaltitleSensorses
dc.publication.volumen17es
dc.publication.issue4es
dc.publication.initialPage1es
dc.publication.endPage25es
dc.contributor.funderMinisterio de Economia, Industria y Competitividad (MINECO). España

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