001437818 000__ 03202cam\a2200565\a\4500
001437818 001__ 1437818
001437818 003__ OCoLC
001437818 005__ 20230309004234.0
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001437818 008__ 210702s2021\\\\sz\\\\\\ob\\\\000\0\eng\d
001437818 019__ $$a1260346536
001437818 020__ $$a9783030765590$$q(electronic bk.)
001437818 020__ $$a3030765598$$q(electronic bk.)
001437818 020__ $$z303076558X
001437818 020__ $$z9783030765583
001437818 0247_ $$a10.1007/978-3-030-76559-0$$2doi
001437818 035__ $$aSP(OCoLC)1258660023
001437818 040__ $$aYDX$$beng$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCQ
001437818 049__ $$aISEA
001437818 050_4 $$aQA402.5
001437818 08204 $$a006.3/824$$223
001437818 1001_ $$aCarabaza, Sara Pérez.
001437818 24510 $$aMulti-UAS minimum time search in dynamic and uncertain environments /$$cSara Pérez Carabaza.
001437818 260__ $$aCham, Switzerland :$$bSpringer,$$c2021.
001437818 300__ $$a1 online resource
001437818 336__ $$atext$$btxt$$2rdacontent
001437818 337__ $$acomputer$$bc$$2rdamedia
001437818 338__ $$aonline resource$$bcr$$2rdacarrier
001437818 4901_ $$aSpringer theses,$$x2190-5053
001437818 500__ $$a"Doctoral thesis accepted by Universidad Complutense de Madrid, Spain."
001437818 504__ $$aIncludes bibliographical references.
001437818 5050_ $$aIntroduction -- State of the Art -- Problem Formulation and Optimization Approach -- MTS Algorithms for Cardinal UAV Motion Models.
001437818 506__ $$aAccess limited to authorized users.
001437818 520__ $$aThis book proposes some novel approaches for finding unmanned aerial vehicle trajectories to reach targets with unknown location in minimum time. At first, it reviews probabilistic search algorithms that have been used for dealing with the minimum time search (MTS) problem, and discusses how metaheuristics, and in particular the ant colony optimization algorithm (ACO), can help to find high-quality solutions with low computational time. Then, it describes two ACO-based approaches to solve the discrete MTS problem and the continuous MTS problem, respectively. In turn, it reports on the evaluation of the ACO-based discrete and continuous approaches to the MTS problem in different simulated scenarios, showing that the methods outperform in most all the cases over other state-of-the-art approaches. In the last part of the thesis, the work of integration of the proposed techniques in the ground control station developed by Airbus to control ATLANTE UAV is reported in detail, providing practical insights into the implementation of these methods for real UAVs.
001437818 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 19, 2021).
001437818 650_0 $$aAnt algorithms.
001437818 650_0 $$aDrone aircraft$$xControl systems.
001437818 650_0 $$aSwarm intelligence.
001437818 650_6 $$aAlgorithmes de colonies de fourmis.
001437818 650_6 $$aDrones$$xSystèmes de commande.
001437818 655_0 $$aElectronic books.
001437818 77608 $$iPrint version: $$z303076558X$$z9783030765583$$w(OCoLC)1247681157
001437818 830_0 $$aSpringer theses,$$x2190-5053
001437818 852__ $$bebk
001437818 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-76559-0$$zOnline Access$$91397441.1
001437818 909CO $$ooai:library.usi.edu:1437818$$pGLOBAL_SET
001437818 980__ $$aBIB
001437818 980__ $$aEBOOK
001437818 982__ $$aEbook
001437818 983__ $$aOnline
001437818 994__ $$a92$$bISE