Cooperative Path Planning of Unmanned Aerial Vehicles E-Book

Antonios Tsourdos

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Aerospace Series (PEP)
• Sprache: Englisch

Seitenzahl: 219

Veröffentlichungsjahr: 2010

Beschreibung

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.

Leseprobe

Table of Contents

Aerospace Series List

Title Page

Copyright

About the Authors

Series Preface

Preface

Acknowledgements

List of Figures

List of Tables

Nomenclature

1. Introduction

1.1 Path Planning Formulation

1.2 Path Planning Constraints

1.3 Cooperative Path Planning and Mission Planning

1.4 Path Planning—An Overview

1.5 The Road Map Method

1.6 Probabilistic Methods

1.7 Potential Field

1.8 Cell Decomposition

1.9 Optimal Control

1.10 Optimization Techniques

1.11 Trajectories for Path Planning

1.12 Outline of the Book

2. Path Planning in Two Dimensions

2.1 Dubins Paths

2.2 Designing Dubins Paths using Analytical Geometry

2.3 Existence of Dubins Paths

2.4 Length of Dubins Path

2.5 Design of Dubins Paths using Principles of Differential Geometry

2.6 Paths of Continuous Curvature

2.7 Producing Flyable Clothoid Paths

2.8 Producing Flyable Pythagorean Hodograph Paths (2D)

3. Path Planning in Three Dimensions

3.1 Dubins Paths in Three Dimensions Using Differential Geometry

3.2 Path Length–Dubins 3D

3.3 Pythagorean Hodograph Paths–3D

3.4 Design of Flyable Paths Using PH Curves

4. Collision Avoidance

4.1 Research into Obstacle Avoidance

4.2 Obstacle Avoidance for Mapped Obstacles

4.3 Obstacle Avoidance of Unmapped Static Obstacles

4.4 Algorithmic Implementation

5. Path-Following Guidance

5.1 Path Following the Dubins Path

5.2 Linear Guidance Algorithm

5.3 Nonlinear Dynamic Inversion Guidance

5.4 Dynamic Obstacle Avoidance Guidance

6. Path Planning for Multiple UAVs

6.1 Problem Formulation

6.2 Simultaneous Arrival

6.3 Phase I: Producing Flyable Paths

6.4 Phase II: Producing Feasible Paths

6.5 Phase III: Equalizing Path Lengths

6.6 Multiple Path Algorithm

6.7 Algorithm Application for Multiple UAVs

6.8 2D Pythagorean Hodograph Paths

6.9 3D Dubins Paths

6.10 3D Pythagorean Hodograph Paths

Appendix A Differential Geometry

A.1 Frenet–Serret Equations

A.2 Importance of Curvature and Torsion

A.3 Motion and Frames

Appendix B Pythagorean Hodograph

B.1 Pythagorean Hodograph

Index

Aerospace Series ListCooperative Path Planning of Unmanned Aerial VehiclesTsourdos et alNovember 2010Principles of Flight for PilotsSwattonOctober 2010Air Travel and Health: A Systems PerspectiveSeabridge et alSeptember 2010Design and Analysis of Composite Structures: With Applications to Aerospace StructuresKassapoglouSeptember 2010Unmanned Aircraft Systems: UAVS Design, Development and DeploymentAustinApril 2010Introduction to Antenna Placement & InstallationsMacnamaraApril 2010Principles of Flight SimulationAllertonOctober 2009Aircraft Fuel SystemsLangton et alMay 2009The Global Airline IndustryBelobabaApril 2009Computational Modelling and Simulation of Aircraft and the Environment: Volume 1—Platform Kinematics and Synthetic EnvironmentDistonApril 2009Handbook of Space TechnologyLey, Wittmann HallmannApril 2009Aircraft Performance Theory and Practice for PilotsSwattonAugust 2008Surrogate Modelling in Engineering Design: A Practical GuideForrester, Sobester, KeaneAugust 2008Aircraft Systems, 3 EditionMoir & SeabridgeMarch 2008Introduction to Aircraft Aeroelasticity And LoadsWright & CooperDecember 2007Stability and Control of Aircraft SystemsLangtonSeptember 2006Military Avionics SystemsMoir & SeabridgeFebruary 2006Design and Development of Aircraft SystemsMoir & SeabridgeJune 2004Aircraft Loading and Structural LayoutHoweMay 2004Aircraft Display Systems JukesDecember 2003Civil Avionics Systems Moir & SeabridgeDecember 2002

This edition first published 2011

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Library of Congress Cataloguing-in-Publication Data

Tsourdos, Antonios.

Cooperative path planning of unmanned aerial vehicles / Antonios Tsourdos, Brian White, Madhavan Shanmugavel.

p. cm.

Includes bibliographical references and index.

ISBN 978-0-470-74129-0 (cloth)

1. Drone aircraft–Automatic control. 2. Guidance systems (Flight) 3. Airplanes–Piloting–Mathematics. 4. Airplanes–Piloting–Planning. 5. Airways–Mathematical models. I. White, Brian, 1947 June 6- II. Shanmugavel, Madhavan. III. Title.

TL589.4.T78 2010

629.132'5—dc22

2010026275

A catalogue record for this book is available from the British Library.

Print ISBN: 978-0-470-74129-0

ePDF ISBN: 978-0-470-97520-6

oBook ISBN: 978-0-470-97463-6

ePub ISBN: 978-0-470-97464-3

About the Authors

Antonios Tsourdos was appointed Head of the Autonomous Systems Group at Cranfield University in 2007. He obtained a PhD on Nonlinear Robust Flight Control Design and Analysis from Cranfield University in 1999. He was a member of the Team Stellar, the winning team for the UK MoD Grand Challenge (2008). He has served as an Editorial Board Member for the Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, the International Journal of Systems Science, the IEEE Transactions on Instrumentation and Measurement, the International Journal on Advances in Intelligent Systems and the international journal Mathematics in Engineering, Science and Aerospace (MESA). He is a member of the A|D|S Autonomous Systems Strategy Group and the A&D KTN National Technical Committee on Autonomous Systems. He is also a member of the IFAC Technical Committee on Aerospace Control, the IFAC Technical Committee on Networked Systems, the AIAA Technical Committee on Guidance, Control & Navigation, the IEEE Control System Society Technical Committee on Aerospace Control (TCAC) and the IEEE Technical Committee on Aerial Robotics and Unmanned Aerial Vehicles.

Brian White obtained a BSc degree in Engineering from the University of Leicester, followed by an MSc and PhD from UMIST, Manchester, in 1974. He has worked in the aerospace industry for the company MBDA, working on novel guidance techniques for missile systems, including one of the first developments of Kalman filters for integration into guidance systems. He has since been a faculty member of the School of Engineering at the University of Bath and at Cranfield University, where for many years he was Head of the Department of Aerospace, Power and Sensors. While in the post, he built up a strong department in Aerospace Systems and also led the Control and Guidance Group, which became a world-leading group in control, navigation and guidance for unmanned aerial vehicles (UAVs). In 2008, he retired, to become Emeritus Professor, retaining a strong interest in research for Autonomy in UAV Systems with the Autonomous Systems Group. He has published well over 100 papers in guidance, control estimation and autonomy, giving invited and keynote lectures at Universities and International Conferences. By gaining research expertise in these multiple domains, he has developed an approach that produces simple, robust and effective approaches to the design of multiple UAV systems. This book expresses some of that wide experience.

Madhavan Shanmugavel is currently a Research Fellow at Cranfield Security and Defence, Defence College of Management and Technology, Cranfield University, Defence Academy of the UK, Shrivenham. He began his research career with Cranfield University in 2007, developing path planning algorithm for unmanned vehicles. He graduated from the Indian Institute of Technology, Chennai, with a Masters Degree in 2000, and gained industrial research experience with TATA Motors, India, since 2004. In his current position, he contributed his knowledge in various projects by extending the path planning algorithms to unmanned ground and aerial vehicles. He has published 14 conference papers, and two journal papers. His research interests include cooperative systems, guidance and control, robotics and path planning of unmanned systems.

Series Preface

The Aerospace Series is a source of aviation and space technology knowledge for business professionals, industry operators and users. The Series topics covered span the design, development, manufacture, operation and support as well as infrastructure operations and developments in research and technology. Authors are drawn from within the aerospace industry as well as from universities and learning institutions from around the world.

The use of Unmanned Aerial Vehicles (UAV's) in modern military conflicts has grown exponentially over the past twenty years and as the autonomous UAV has replaced the human operator in a fast growing number of military flight operations the need for effective and efficient mission management of UAV's has become critical. One key area of developing technology associated with this requirement is “Path Planning” which is the subject addressed by this book. Here the authors Antonios Tsourdos, Brian White and Madhavan Shanmugavel provide a thorough and complete treatment of the subject from its inception in ground-based robotics to the path planning needs of the modern UAV covering kinematic and environmental constraints, safety and mission/path coordination, 2-D and 3-D path planning techniques. Sense and avoid considerations are also included. Cooperative Path Planning of Unmanned Aerial Vehicles promises to be an important reference for practitioners in the growing field of autonomous air vehicles.

Allan Seabridge, Roy Langton, Jonathan Cooper and Peter Belobaba

Preface

Path planning is a complex problem, which involves meeting the physical constraints of the unmanned aerial vehicles (UAVs), constraints from the operating environment and other operational requirements. The foremost constraint to be met is that the paths must be flyable. Flyable paths are those that meet the kinematic constraints of the UAV. Satisfying this constraint ensures that the motion of the UAV stays within the maximum bounds on manoeuvre curvature. The safety of the path is measured by the ability of the path to avoid threats, obstacles and other UAVs. The path must maintain collision avoidance with other friendly UAVs and also must be flexible enough to avoid environmental obstacles and threats. Also, additional constraints—such as generating shortest paths, and minimum fuel and energy consumption paths—can be included for better performance and efficiency of the mission.

This book has grown out of the research work of the authors in the area of path planning, collision avoidance and path following for single and multiple unmanned vehicles in the past ten years. The algorithms described here result in the planning of paths that are not only flyable and safe but also implementable for real-time applications.

Antonios Tsourdos

Brian White

Madhavan Shanmugavel

Acknowledgements

We would like to thank our colleagues who helped us to develop the path planning algorithms described in this book. In particular, we would like to thank Hyo Sang Shin, Luigi Caravita, Matt Robb, Seung Keun Kim, Samuel Lazarus and Arpita Sinha.

List of Figures

1.1A block diagram approach to path planning1.2Autopilot and guidance control loops1.3Curvature and torsion1.4Hierarchy of mission planning1.5Existing approach to path planning1.6The road map method1.7Visibility graph1.8Voronoi diagram: polygonal fences around obstacles1.9Cell decomposition2.1CLC and CCC types of Dubins path2.2Tangent circles2.3Dubins path with external tangent2.4Dubins path with internal tangent2.5Block diagram of path planner to generate the shortest flyable paths2.6Dubins paths with as a free variable. The start turn is either clockwise or anticlockwise. Four possible turns on each tangent circle produce eight paths2.7Dubins arc geometry2.8Set of Dubins paths over a range of