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001 9781003026686
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008 200404s2020 flu ob 001 0 eng d
040 _aOCoLC-P
_beng
_cOCoLC-P
020 _a9781000049985
_q(electronic bk.)
020 _a1000049981
_q(electronic bk.)
020 _a9781003026686
_q(electronic bk.)
020 _a1003026680
_q(electronic bk.)
020 _a9781000049909
_q(electronic bk. : PDF)
020 _a1000049906
_q(electronic bk. : PDF)
020 _z9780367457822
020 _z0367457822
035 _a(OCoLC)1148110907
035 _a(OCoLC-P)1148110907
050 4 _aTL685.35
072 7 _aCOM
_x012040
_2bisacsh
072 7 _aCOM
_x037000
_2bisacsh
072 7 _aCOM
_x044000
_2bisacsh
072 7 _aUMB
_2bicssc
082 0 4 _a629.133/39
_223
100 1 _aBestaoui Sebbane, Yasmina,
_eauthor.
245 1 0 _aMulti-UAV planning and task allocation
_h[electronic resource] /
_cYasmina Bestaoui-Sebbane.
264 1 _aBoca Raton :
_bCRC Press,
_c2020.
300 _a1 online resource.
490 1 _aChapman & Hall/CRC artificial intelligence and robotics series
505 0 _aIntro -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Author -- Chapter 1 Multi-Aerial-Robot Planning -- 1.1 Introduction -- 1.2 Team Approach -- 1.2.1 Cooperation -- 1.2.2 Cascade-Type Guidance Law -- 1.2.3 Consensus Approach -- 1.2.3.1 Consensus Opinion -- 1.2.3.2 Reachability and Observability -- 1.2.4 Flocking Behavior -- 1.2.4.1 Collective Potential of Flocks -- 1.2.4.2 Distributed Flocking Algorithms -- 1.2.5 Connectivity and Convergence of Formations -- 1.2.5.1 Problem Formulation -- 1.2.5.2 Stability of Formations in Time-Invariant Communication
505 8 _a1.3 Deterministic Decision-Making -- 1.3.1 Distributed Receding Horizon Control -- 1.3.2 Conflict Resolution -- 1.3.2.1 Distributed Reactive Collision Avoidance -- 1.3.2.2 Deconfliction Maintenance -- 1.3.3 Artificial Potential -- 1.3.3.1 Velocity Field -- 1.3.3.2 Artificial Potential Field -- 1.3.3.3 Pattern Formation and Reconfigurability -- 1.3.4 Symbolic Planning -- 1.4 Association with Limited Communication -- 1.4.1 Introduction -- 1.4.2 Problem Formulation -- 1.4.2.1 Decentralized Resolution of Inconsistent Association -- 1.4.3 Genetic Algorithms -- 1.4.4 Games Theory Reasoning
505 8 _a1.4.4.1 Cooperative Protocol -- 1.4.4.2 Non-Cooperative Protocol -- 1.4.4.3 Leader/Follower Protocol -- 1.5 Multiagent Decision-Making under Uncertainty -- 1.5.1 Decentralized Team Decision Problem -- 1.5.1.1 Bayesian Strategy -- 1.5.1.2 Semi-Modeler Strategy -- 1.5.1.3 Communication Models -- 1.5.2 Algorithms for Optimal Planning -- 1.5.2.1 Multiagent A* (MAA*): A Heuristic Search Algorithm for DEC-POMDP -- 1.5.2.2 Policy Iteration for Infinite Horizon -- 1.5.2.3 Linear-Quadratic Approach -- 1.5.2.4 Decentralized Chance-Constrained Finite Horizon Optimal Control
505 8 _a1.5.3 Task Allocation: Optimal Assignment -- 1.5.3.1 Hungarian Algorithm -- 1.5.3.2 Interval Hungarian Algorithm -- 1.5.3.3 Quantifying the Effect of Uncertainty -- 1.5.3.4 Uncertainty Measurement for a Single Utility -- 1.5.4 Distributed Chance-Constrained Task Allocation -- 1.5.4.1 Chance-Constrained Task Allocation -- 1.5.4.2 Distributed Approximation to the Chance-Constrained Task Allocation Problem -- 1.6 Case Studies -- 1.6.1 Reconnaissance Mission -- 1.6.1.1 General Vehicle Routing Problem -- 1.6.1.2 Chinese Postman Problem -- 1.6.1.3 Cluster Algorithm -- 1.6.1.4 The Rural CPP
505 8 _a1.6.2 Expanding Grid Coverage -- 1.6.3 Optimization of Perimeter Patrol Operations -- 1.6.3.1 Multiagent Markov Decision Process -- 1.6.3.2 Anytime Error Minimization Search -- 1.6.4 Stochastic Strategies for Surveillance -- 1.6.4.1 Analysis Methods -- 1.6.4.2 Problems in 1D -- 1.6.4.3 Complete Graphs -- 1.7 Conclusions -- Chapter 2 Flight Planning -- 2.1 Introduction -- 2.2 Path and Trajectory Planning -- 2.2.1 Trim Trajectories -- 2.2.2 Trajectory Planning -- 2.2.2.1 Time Optimal Trajectories -- 2.2.2.2 Nonholonomic Motion Planning -- 2.2.3 Path Planning -- 2.2.3.1 B-Spline Formulation
520 _aMulti-robot systems are a major research topic in robotics. Designing, testing, and deploying aerial robots in the real world is a possibility due to recent technological advances. This book explores different aspects of cooperation in multiagent systems. It covers the team approach as well as deterministic decision-making. It also presents distributed receding horizon control, as well as conflict resolution, artificial potentials, and symbolic planning. The book also covers association with limited communications, as well as genetic algorithms and game theory reasoning. Multiagent decision-making and algorithms for optimal planning are also covered along with case studies. Key features: Provides a comprehensive introduction to multi-robot systems planning and task allocation Explores multi-robot aerial planning; flight planning; orienteering and coverage; and deployment, patrolling, and foraging Includes real-world case studies Treats different aspects of cooperation in multiagent systems Both scientists and practitioners in the field of robotics will find this text valuable.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aDrone aircraft
_xAutomatic control.
650 0 _aMultiagent systems.
650 0 _aAdaptive control systems.
650 7 _aCOMPUTERS / Computer Graphics / Game Programming & Design
_2bisacsh
650 7 _aCOMPUTERS / Machine Theory
_2bisacsh
650 7 _aCOMPUTERS / Neural Networks
_2bisacsh
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003026686
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c127634
_d127634