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dc.contributor.authorRamírez Atencia, Cristian Oliver
dc.contributor.authorBello Orgaz, Gema 
dc.contributor.authorR-Moreno, María Dolores
dc.contributor.authorCamacho, David
dc.contributor.otherUAM. Departamento de Ingeniería Informáticaes_ES
dc.date.accessioned2015-03-25T18:44:00Z
dc.date.available2015-03-25T18:44:00Z
dc.date.issued2014
dc.identifier.citationIntelligent Data Engineering and Automated Learning – IDEAL 2014: 15th International Conference, Salamanca, Spain, September 10-12, 2014. Proceedings. Lecture Notes in Computer Science, Volumen 8669. Springer, 2014. 286-294.en_US
dc.identifier.isbn978-3-319-10839-1 (print)en_US
dc.identifier.isbn978-3-319-10840-7 (online)en_US
dc.identifier.issn0302-9743 (print)en_US
dc.identifier.issn1611-3349 (online)en_US
dc.identifier.urihttp://hdl.handle.net/10486/664809
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-10840-7_35en_US
dc.descriptionProceedings 15th International Conference, Salamanca, Spain, September 10-12, 2014.en_US
dc.description.abstractMission Planning is a classical problem that has been traditionally studied in several cases from Robotics to Space missions. This kind of problems can be extremely difficult in real and dynamic scenarios. This paper provides a first analysis for mission planning to Unmanned Air Vehicles (UAVs), where sensors and other equipment of UAVs to perform a task are modelled based on Temporal Constraint Satisfaction Problems (TCSPs). In this model, a set of resources and temporal constraints are designed to represent the main characteristics (task time, fuel consumption, ...) of this kind of aircrafts. Using this simplified TCSP model, and a Branch and Bound (B&B) search algorithm, a set of feasible solutions will be found trying to minimize the fuel cost, flight time spent and the number of UAVs used in the mission. Finally, some experiments will be carried out to validate both the quality of the solutions found and the spent runtime to found them.en_US
dc.description.sponsorshipThis work is supported by the Spanish Ministry of Science and Education under Project Code TIN2010-19872 and Savier Project (Airbus Defence & Space, FUAM-076915).en_US
dc.format.extent9 pág.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringer Berlin Heidelberg
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rights© Springer-Verlag Berlin Heidelberg 2014
dc.subject.otherUnmanned aircraft systemsen_US
dc.subject.otherMission planningen_US
dc.subject.otherTemporal constraint satisfaction problemsen_US
dc.subject.otherBranch and bounden_US
dc.titleBranching to find feasible solutions in unmanned air vehicle mission planningen_US
dc.typeconferenceObjecten
dc.typebookParten
dc.subject.ecienciaInformáticaes_ES
dc.date.embargoend2015-10-01
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-319-10840-7_35
dc.identifier.doi10.1007/978-3-319-10840-7_35
dc.identifier.publicationfirstpage286
dc.identifier.publicationlastpage294
dc.identifier.publicationvolume8669
dc.relation.eventdateSeptember 10-12, 2014en_US
dc.relation.eventnumber15
dc.relation.eventplaceSalamanca (Spain)en_US
dc.relation.eventtitle15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014en_US
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.contributor.groupAnálisis de Datos e Inteligencia Aplicada (ING EPS-012)es_ES
dc.rights.accessRightsopenAccessen
dc.authorUAMCamacho Fernández, David (261274)
dc.authorUAMBello Orgaz, Gema (262523)
dc.facultadUAMEscuela Politécnica Superior


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