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E-raamat: Cooperative Path Planning of Unmanned Aerial Vehicles

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Series edited by (MIT), Series edited by (Parker Aerospace Group, USA), Series edited by (BAE Systems, UK), (Cranfield University, UK), (Cranfield University, UK), (Cranfield University, UK), Series edited by (University Of Liverpool)
  • Formaat: PDF+DRM
  • Sari: Aerospace Series
  • Ilmumisaeg: 12-Oct-2010
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9780470975206
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Cooperative Path Planning of Unmanned Aerial VehiclesSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Aerospace Series
  • Ilmumisaeg: 12-Oct-2010
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9780470975206
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An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in the area of cooperative systems, cooperative control and optimization particularly in the aerospace industry.
About the Authors ix
Series Preface xi
Preface xii
Acknowledgements xiii
List of Figures
xv
List of Tables
xxi
Nomenclature xxiii
1 Introduction
1(28)
1.1 Path Planning Formulation
2(1)
1.2 Path Planning Constraints
3(4)
1.2.1 Flyable Paths: Capturing Kinematics
4(2)
1.2.2 UAV Inertial Manoeuvre Coordinates
6(1)
1.2.3 Generation of Safe Paths for Path Planning
7(1)
1.3 Cooperative Path Planning and Mission Planning
7(3)
1.4 Path Planning - An Overview
10(3)
1.5 The Road Map Method
13(3)
1.5.1 Visibility Graphs
14(1)
1.5.2 Voronoi Diagrams
14(2)
1.6 Probabilistic Methods
16(1)
1.7 Potential Field
16(1)
1.8 Cell Decomposition
17(1)
1.9 Optimal Control
18(1)
1.10 Optimization Techniques
18(1)
1.11 Trajectories for Path Planning
19(1)
1.12 Outline of the Book
20(2)
References
22(7)
2 Path Planning in Two Dimensions
29(36)
2.1 Dubins Paths
30(1)
2.2 Designing Dubins Paths using Analytical Geometry
31(6)
2.2.1 Dubins Path: External Tangent Solution
33(2)
2.2.2 Dubins Path: Internal Tangent Solution
35(2)
2.3 Existence of Dubins Paths
37(2)
2.4 Length of Dubins Path
39(1)
2.5 Design of Dubins Paths using Principles of Differential Geometry
39(6)
2.5.1 Dubins Path Length
43(2)
2.6 Paths of Continuous Curvature
45(1)
2.7 Producing Flyable Clothoid Paths
46(10)
2.8 Producing Flyable Pythagorean Hodograph Paths (2D)
56(6)
2.8.1 Design of Flyable Path using 2D PH curve
61(1)
References
62(3)
3 Path Planning in Three Dimensions
65(16)
3.1 Dubins Paths in Three Dimensions Using Differential Geometry
67(5)
3.2 Path Length-Dubins 3D
72(1)
3.3 Pythagorean Hodograph Paths-3D
72(2)
3.3.1 Spatial PH Curves
73(1)
3.4 Design of Flyable Paths Using PH Curves
74(4)
3.4.1 Design of Flyable Paths
75(3)
References
78(3)
4 Collision Avoidance
81(38)
4.1 Research into Obstacle Avoidance
83(2)
4.2 Obstacle Avoidance for Mapped Obstacles
85(18)
4.2.1 Line Intersection Detection
86(4)
4.2.2 Line Segment Intersection
90(4)
4.2.3 Arc Intersection
94(9)
4.3 Obstacle Avoidance of Unmapped Static Obstacles
103(3)
4.3.1 Safety Circle Algorithm
104(1)
4.3.2 Intermediate Waypoint Algorithm
104(2)
4.4 Algorithmic Implementation
106(9)
4.4.1 Dubins Path Modification
107(1)
4.4.2 Clothoid Path Modification
107(3)
4.4.3 PH Path Modification
110(2)
4.4.4 Obstacle Avoidance in 3D
112(3)
References
115(4)
5 Path-Following Guidance
119(28)
5.1 Path Following the Dubins Path
120(4)
5.2 Linear Guidance Algorithm
124(2)
5.3 Nonlinear Dynamic Inversion Guidance
126(6)
5.4 Dynamic Obstacle Avoidance Guidance
132(13)
5.4.1 UAV Direction Control
135(7)
5.4.2 Multiple Conflict Resolution
142(3)
References
145(2)
6 Path Planning for Multiple UAVs
147(28)
6.1 Problem Formulation
149(2)
6.2 Simultaneous Arrival
151(1)
6.3 Phase I: Producing Flyable Paths
152(1)
6.4 Phase II: Producing Feasible Paths
152(4)
6.4.1 Minimum Separation Distance
153(1)
6.4.2 Non-Intersection Paths
154(1)
6.4.3 Offset Curves
155(1)
6.5 Phase III: Equalizing Path Lengths
156(1)
6.6 Multiple Path Algorithm
156(1)
6.7 Algorithm Application for Multiple UAVs
157(5)
6.7.1 2D Dubins Paths
157(3)
6.7.2 2D Clothoid Paths
160(2)
6.8 2D Pythagorean Hodograph Paths
162(3)
6.9 3D Dubins Paths
165(4)
6.10 3D Pythagorean Hodograph Paths
169(5)
References
174(1)
Appendix A Differential Geometry
175(8)
A.1 Frenet-Serret Equations
177(1)
A.2 Importance of Curvature and Torsion
178(1)
A.3 Motion and Frames
179(2)
References
181(2)
Appendix B Pythagorean Hodograph
183(4)
B.1 Pythagorean Hodograph
184(1)
References
185(2)
Index 187
Antonios Tsourdos is a Reader in Autonomous Systems and Control and Head of the Guidance and Control Group at Cranfield. His research areas include UAV Autonomy, UAV Path Planning, Coordinated Guidance, Cooperative Control, UAV Swarm, Autonomous Sensors Network, Sensor and Data Fusion, and Vehicle Health Management. He has authored many scientific research papers and has served as a guest editor for journal special issues on 'multi-vehicle systems cooperative control with applications'; 'advances in missile guidance and control: theory and practice', and cooperative control approaches for multiple mobile robots'. Brian A White, now Professor Emeritus at Cranfield, was until recently Head of the Department of Aerospace, Power and Sensors and also Head of the Guidance and Control Group at Cranfield. His areas of expertise are robust control, non-linear control, estimation, observer applications, inertial navigation, guidance design, soft computing and sensor and data fusion. He has published widely in the control science field, mainly on autopilot design and guidance. He has managed significant contracts in the area of guidance. He has organized and run numerous invited sessions at major control conferences and co-edited a special issue of the IFAC journal Control Engineering Practice on Control in Defence Systems. He has served as associate editor for the IMechE Journal of Aerospace Engineering (Part G), IMechE Journal of Systems and Control Engineering (Part I), and the Journal of Nonlinear Studies.

Madhavan Shanmugavel is a Research Officer within the Guidance and Control Group at Cranfield.
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