Cooperative Path Planning of Unmanned Aerial

Path Planning Strategies for Cooperative Autonomous Air Vehicles offers a dedicated, practical guide to computational path planning for cooperative autonomous vehicles. Focuses on the path planning of multiple UAVs for simultaneous arrival on target, it also offers coverage of path planners that are applicable to land, sea, or spaceborne vehicles. The authors divide the solution to path planning into two phases: first, the paths are produced to meet curvature constraints the flyable paths and second, the flyable paths are tuned to meet the mission. They describe approaches that use both composite and single curves, and extend these approaches to cater for the complex issue of sense and avoid. Authored by a leading group of researchers at Cranfield, this book presents an invaluable new addition to the existing literature on UAV guidance and cooperative control. There is an increasing interest in the potential of UAV (unmanned air vehicles) and MAV (micro air vehicle) technology Dedicated, practical guide to computational path planning for cooperative autonomous vehicles offering an invaluable resource for UAV researchers and practitioners Includes chapters on path planning, 3D path planning, cooperative path planning, path planning in complex environments and sense & avoid Describes pathplanners applicable to other types of autonomous vehicles beyond those that are airborne, including those that are land, air or spaceborne

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.

Preface
Acknowledgements
Introduction
Path Planning Formulation
Path Planning Constraints
Cooperative Path Planning and Mission Planning
Path Planning - An Overview
The Road Map Method
Probabilistic Methods
Potential Field
Cell Decomposition
Optimal Control
Optimisation Techniques
Trajectories for path planning
Outline of the book
References
Path planning in Two Dimensions
Dubins Paths 25
Designing Dubins Paths using Analytical Geometry
Existence of Dubins Paths
Length of Dubins path
Design of Dubins Paths using principles of Differential Geometry
Paths of Continuous Curvature
Producing Flyable Clothoid Paths
Producing Flyable Pythagorean Hodograph Paths (2D)
References
Path Planning in Three Dimensions
Dubins Paths in Three Dimensions using Differential Geometry
Path Length - Dubins 3D
Pythagorean Hodograph Paths-3D
Design of Flyable Paths using PH curves
References
Collision Avoidance
Research into Obstacle Avoidance
Obstacle Avoidance for Mapped Obstacles
Obstacle Avoidance of Unmapped Static Obstacles
Algorithmic Implementation
References
Path Following Guidance
Path following the Dubins path
Linear Guidance Algorithm
Nonlinear Dynamic Inversion Guidance
Dynamic Obstacle Avoidance Guidance
References
Path planning for Multiple UAVs
Problem formulation
Simultaneous Arrival
Phase I: Producing Flyable Paths
Phase II: Producing Feasible Paths
Phase III: Equalising Path Lengths
Multiple Path Algorithm
Algorithm Application for Multiple UAVs
2D Pythagorean Hodographs Paths
3D Dubins Paths
3D Pythagorean Hodograph Paths
References
Differential geometry
Frenet Serret equations
Importance of Curvature and Torsion
Motion and Frames

Pythagorean Hodograph
Pythagorean Hodograph
References
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Cooperative Path Planning of Unmanned Aerial Vehicles

Summary

Author Biography

Table of Contents

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