000 03815nam a22005415i 4500
001 978-3-319-63604-7
003 DE-He213
005 20220801221210.0
007 cr nn 008mamaa
008 170803s2018 sz | s |||| 0|eng d
020 _a9783319636047
_9978-3-319-63604-7
024 7 _a10.1007/978-3-319-63604-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aAltshuler, Yaniv.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_954658
245 1 0 _aSwarms and Network Intelligence in Search
_h[electronic resource] /
_cby Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aIX, 238 p. 116 illus., 53 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v729
505 0 _aIntroduction to Swarm Search -- Cooperative “Swarm Cleaning” of Stationary Domains -- Swarm Search of Expanding Regions in Grids: Lower Bounds -- Swarm Search of Expanding Regions in Grids: Upper Bounds -- The Search Complexity of Collaborative Swarms Expanding Z2 Grid Regions.
520 _aThis book offers a comprehensive analysis of the theory and tools needed for the development of an efficient and robust infrastructure for the design of collaborative patrolling unmanned aerial vehicle (UAV) swarms, focusing on its applications for tactical intelligence drones. It discusses frameworks for robustly and near-optimally analyzing flocks of semi-autonomous vehicles designed to efficiently perform the ongoing dynamic patrolling and scanning of pre-defined “search regions”. It discusses the theoretical limitations of such systems, as well as the trade-offs between the systems’ various economic and operational parameters. Current UAV systems rely mainly on human operators for the design and adaptation of drones’ flying routes. However, recent technological advances have introduced new systems, comprised of a small number of self-organizing vehicles, manually guided at the swarm level by a human operator. With the growing complexity of such man-supervised architectures, it is becoming increasingly harder to guarantee a pre-defined level of performance. The use of large scale swarms of UAVs as a combat and reconnaissance platform therefore necessitates the development of an efficient optimization mechanism of their utilization, specifically in the design and maintenance of their patrolling routes. The book is intended for researchers and engineers in the fields of swarms systems and autonomous drones. .
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aPentland, Alex.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_954659
700 1 _aBruckstein, Alfred M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_954660
710 2 _aSpringerLink (Online service)
_954661
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319636023
776 0 8 _iPrinted edition:
_z9783319636030
776 0 8 _iPrinted edition:
_z9783319875910
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v729
_954662
856 4 0 _uhttps://doi.org/10.1007/978-3-319-63604-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79400
_d79400