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005 20200520144314.0
010   $a1-68015-897-X
010   $a1-282-45820-5
010   $a1-282-93575-5
010   $a9786612458200
010   $a9786612935756
010   $a1-4008-3147-4
010   $a0-691-14195-9
024 7 $a10.1515/9781400831470
035   $a(CKB)2550000000007546
035   $a(EBL)483500
035   $a(OCoLC)609855940
035   $a(SSID)ssj0000358952
035   $a(PQKBManifestationID)11925424
035   $a(PQKBTitleCode)TC0000358952
035   $a(PQKBWorkID)10378914
035   $a(PQKB)11435001
035   $a(DE-B1597)446779
035   $a(OCoLC)979835075
035   $a(DE-B1597)9781400831470
035   $a(Au-PeEL)EBL483500
035   $a(CaPaEBR)ebr10364752
035   $a(CaONFJC)MIL293575
035   $a(Au-PeEL)EBL4968545
035   $a(CaONFJC)MIL245820
035   $a(OCoLC)741250474
035   $z(PPN)199244367
035   $a(PPN)187953694
035   $a(FR-PaCSA)88838005
035   $a(MiAaPQ)EBC483500
035   $a(EXLCZ)992550000000007546
100   $a20090212d2009      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aDistributed control of robotic networks $ea mathematical approach to motion coordination algorithms /$fFrancesco Bullo, Jorge Corte?s, Sonia Marti?nez
205   $aCourse Book
210   $aPrinceton, NJ $cPrinceton University Press$d2009
215   $a1 online resource (333 p.)
225 1 $aPrinceton series in applied mathematics
300   $aDescription based upon print version of record.
320   $aIncludes bibliographical references and index.
327   $t Frontmatter -- $tContents -- $tPreface -- $tChapter One. An introduction to distributed algorithms -- $tChapter Two. Geometric models and optimization -- $tChapter Three. Robotic network models and complexity notions -- $tChapter Four. Connectivity maintenance and rendezvous -- $tChapter Five. Deployment -- $tChapter Six. Boundary estimation and tracking -- $tBibliography -- $tAlgorithm Index -- $tSubject Index -- $tSymbol Index
330   $aThis self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms. Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises. Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation 
410  0$aPrinceton series in applied mathematics.
606   $aRobotics
606   $aComputer algorithms
606   $aRobots$xControl systems
610   $a1-center problem.
610   $aAdjacency matrix.
610   $aAggregate function.
610   $aAlgebraic connectivity.
610   $aAlgebraic topology (object).
610   $aAlgorithm.
610   $aAnalysis of algorithms.
610   $aApproximation algorithm.
610   $aAsynchronous system.
610   $aBellman?Ford algorithm.
610   $aBifurcation theory.
610   $aBounded set (topological vector space).
610   $aCalculation.
610   $aCartesian product.
610   $aCentroid.
610   $aChebyshev center.
610   $aCirculant matrix.
610   $aCircumscribed circle.
610   $aCluster analysis.
610   $aCombinatorial optimization.
610   $aCombinatorics.
610   $aCommunication complexity.
610   $aComputation.
610   $aComputational complexity theory.
610   $aComputational geometry.
610   $aComputational model.
610   $aComputer simulation.
610   $aComputer vision.
610   $aConnected component (graph theory).
610   $aConnectivity (graph theory).
610   $aConsensus (computer science).
610   $aControl function (econometrics).
610   $aDifferentiable function.
610   $aDijkstra's algorithm.
610   $aDimensional analysis.
610   $aDirected acyclic graph.
610   $aDirected graph.
610   $aDiscrete time and continuous time.
610   $aDisk (mathematics).
610   $aDistributed algorithm.
610   $aDoubly stochastic matrix.
610   $aDynamical system.
610   $aEigenvalues and eigenvectors.
610   $aEstimation.
610   $aEuclidean space.
610   $aFunction composition.
610   $aHybrid system.
610   $aInformation theory.
610   $aInitial condition.
610   $aInstance (computer science).
610   $aInvariance principle (linguistics).
610   $aInvertible matrix.
610   $aIteration.
610   $aIterative method.
610   $aKinematics.
610   $aLaplacian matrix.
610   $aLeader election.
610   $aLinear dynamical system.
610   $aLinear interpolation.
610   $aLinear programming.
610   $aLipschitz continuity.
610   $aLyapunov function.
610   $aMarkov chain.
610   $aMathematical induction.
610   $aMathematical optimization.
610   $aMobile robot.
610   $aMotion planning.
610   $aMulti-agent system.
610   $aNetwork model.
610   $aNetwork topology.
610   $aNorm (mathematics).
610   $aNumerical integration.
610   $aOptimal control.
610   $aOptimization problem.
610   $aParameter (computer programming).
610   $aPartition of a set.
610   $aPercolation theory.
610   $aPermutation matrix.
610   $aPolytope.
610   $aProportionality (mathematics).
610   $aQuantifier (logic).
610   $aQuantization (signal processing).
610   $aRobustness (computer science).
610   $aScientific notation.
610   $aSensor.
610   $aSet (mathematics).
610   $aSimply connected space.
610   $aSimulation.
610   $aSimultaneous equations.
610   $aState space.
610   $aState variable.
610   $aStochastic matrix.
610   $aStochastic.
610   $aStrongly connected component.
610   $aSynchronous network.
610   $aTheorem.
610   $aTime complexity.
610   $aTopology.
610   $aVariable (mathematics).
610   $aVector field.
615  0$aRobotics.
615  0$aComputer algorithms.
615  0$aRobots$xControl systems.
676   $a629.8/9246
686   $aSK 880$2rvk
700   $aBullo$b Francesco$0496801
701   $aCorte?s$b Jorge$f1974-$01615338
701   $aMarti?nez$b Sonia$f1974-$01615339
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910814324103321
996   $aDistributed control of robotic networks$93945484
997   $aUNINA