Sense and Avoid in UAS (eBook, ePUB)

Research and Applications
Redaktion: Angelov, Plamen

• Format: ePub

Produktbeschreibung

There is increasing interest in the potential of UAV (Unmanned Aerial Vehicle) and MAV (Micro Air Vehicle) technology and their wide ranging applications including defence missions, reconnaissance and surveillance, border patrol, disaster zone assessment and atmospheric research. High investment levels from the military sector globally is driving research and development and increasing the viability of autonomous platforms as replacements for the remotely piloted vehicles more commonly in use. UAV/UAS pose a number of new challenges, with the autonomy and in particular collision avoidance, detect and avoid, or sense and avoid, as the most challenging one, involving both regulatory and technical issues. Sense and Avoid in UAS: Research and Applications covers the problem of detect, sense and avoid in UAS (Unmanned Aircraft Systems) in depth and combines the theoretical and application results by leading academics and researchers from industry and academia. Key features: * Presents a holistic view of the sense and avoid problem in the wider application of autonomous systems * Includes information on human factors, regulatory issues and navigation, control, aerodynamics and physics aspects of the sense and avoid problem in UAS * Provides professional, scientific and reliable content that is easy to understand, and * Includes contributions from leading engineers and researchers in the field Sense and Avoid in UAS: Research and Applications is an invaluable source of original and specialised information. It acts as a reference manual for practising engineers and advanced theoretical researchers and also forms a useful resource for younger engineers and postgraduate students. With its credible sources and thorough review process, Sense and Avoid in UAS: Research and Applications provides a reliable source of information in an area that is fast expanding but scarcely covered.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 256
• Erscheinungstermin: 16. März 2012
• Englisch
• ISBN-13: 9781119967842
• Artikelnr.: 37345299

Autorenporträt

Plamen Parvanov Angelov, Lancaster University, UK Plamen Parvanov is a senior lecturer in the School of Computing and Communications at Lancaster University. He is an Associate Editor of three international journals and the founding co-Editor-in-Chief of the Springer journal Evolving Systems. He is also the Vice Chair of the Technical Committee on Standards, Computational Intelligence Society, IEEE and co-Chair of several IEEE conferences. His research in UAV/UAS is often publicised in external publications, e.g. the prestigious Computational Intelligence Magazine; Aviation Week, Flight Global, Airframer, Flight International, etc. His research focuses on computational intelligence and evolving systems, and his research in to autonomous systems has received worldwide recognition. As the Principle Investigator at Lancaster University for a team working on UAV Sense and Avoid fortwo projects of ASTRAEA his work was recognised by 'The Engineer Innovation and Technology 2008 Award in two categories: i) Aerospace and Defence and ii) The Special Award which is an outstanding achievement.

Inhaltsangabe

Preface xv About the Editor xix About the Contributors xxi Part I
Introduction 1 Introduction 3 George Limnaios, Nikos Tsourveloudis and
Kimon P. Valavanis 1.1 UAV versus UAS 3 1.2 Historical Perspective on
Unmanned Aerial Vehicles 5 1.3 UAV Classification 9 1.4 UAV Applications 14
1.5 UAS Market Overview 17 1.6 UAS Future Challenges 20 1.7 Fault Tolerance
for UAS 26 References 31 2 Performance Tradeoffs and the Development of
Standards 35 Andrew Zeitlin 2.1 Scope of Sense and Avoid 35 2.2 System
Configurations 36 2.3 S&A Services and Sub-functions 38 2.4 Sensor
Capabilities 39 2.4.1 Airborne Sensing 39 2.4.2 Ground-Based Sensing 41
2.4.3 Sensor Parameters 41 2.5 Tracking and Trajectory Prediction 42 2.6
Threat Declaration and Resolution Decisions 43 2.6.1 Collision Avoidance 43
2.6.2 Self-separation 45 2.6.3 Human Decision versus Algorithm 45 2.7 Sense
and Avoid Timeline 46 2.8 Safety Assessment 48 2.9 Modeling and Simulation
49 2.10 Human Factors 50 2.11 Standards Process 51 2.11.1 Description 51
2.11.2 Operational and Functional Requirements 52 2.11.3 Architecture 52
2.11.4 Safety, Performance, and Interoperability Assessments 52 2.11.5
Performance Requirements 52 2.11.6 Validation 53 2.12 Conclusion 54
References 54 3 Integration of SAA Capabilities into a UAS Distributed
Architecture for Civil Applications 55 Pablo Royo, Eduard Santamaria, Juan
Manuel Lema, Enric Pastor and Cristina Barrado 3.1 Introduction 55 3.2
System Overview 57 3.2.1 Distributed System Architecture 58 3.3 USAL
Concept and Structure 59 3.4 Flight and Mission Services 61 3.4.1 Air
Segment 61 3.4.2 Ground Segment 65 3.5 Awareness Category at USAL
Architecture 68 3.5.1 Preflight Operational Procedures: Flight Dispatcher
70 3.5.2 USAL SAA on Airfield Operations 72 3.5.3 Awareness Category during
UAS Mission 75 3.6 Conclusions 82 Acknowledgments 82 References 82 Part II
Regulatory Issues and Human Factors 4 Regulations and Requirements 87
Xavier Prats, Jorge Ramirez, Luis Delgado and Pablo Royo 4.1 Background
Information 88 4.1.1 Flight Rules 90 4.1.2 Airspace Classes 91 4.1.3 Types
of UAS and their Missions 93 4.1.4 Safety Levels 96 4.2 Existing
Regulations and Standards 97 4.2.1 Current Certification Mechanisms for UAS
99 4.2.2 Standardization Bodies and Safety Agencies 102 4.3 Sense and Avoid
Requirements 103 4.3.1 General Sense Requirements 103 4.3.2 General
Avoidance Requirements 106 4.3.3 Possible SAA Requirements as a Function of
the Airspace Class 108 4.3.4 Possible SAA Requirements as a Function of the
Flight Altitude and Visibility Conditions 109 4.3.5 Possible SAA
Requirements as a Function of the Type of Communications Relay 110 4.3.6
Possible SAA Requirements as a Function of the Automation Level of the UAS
111 4.4 Human Factors and Situational Awareness Considerations 112 4.5
Conclusions 113 Acknowledgments 114 References 115 5 Human Factors in UAV
119 Marie Cahillane, Chris Baber and Caroline Morin 5.1 Introduction 119
5.2 Teleoperation of UAVs 122 5.3 Control of Multiple Unmanned Vehicles 123
5.4 Task-Switching 124 5.5 Multimodal Interaction with Unmanned Vehicles
127 5.6 Adaptive Automation 128 5.7 Automation and Multitasking 129 5.8
Individual Differences 131 5.8.1 Attentional Control and Automation 131
5.8.2 Spatial Ability 134 5.8.3 Sense of Direction 135 5.8.4 Video Games
Experience 135 5.9 Conclusions 136 References 137 Part III SAA
Methodologies 6 Sense and Avoid Concepts: Vehicle-Based SAA Systems
(Vehicle-to-Vehicle) 145 Stepan Kopriva, David Sislak and Michal Pechoucek
6.1 Introduction 145 6.2 Conflict Detection and Resolution Principles 146
6.2.1 Sensing 146 6.2.2 Trajectory Prediction 147 6.2.3 Conflict Detection
148 6.2.4 Conflict Resolution 149 6.2.5 Evasion Maneuvers 150 6.3
Categorization of Conflict Detection and Resolution Approaches 150 6.3.1
Taxonomy 150 6.3.2 Rule-Based Methods 151 6.3.3 Game Theory Methods 152
6.3.4 Field Methods 153 6.3.5 Geometric Methods 154 6.3.6 Numerical
Optimization Approaches 156 6.3.7 Combined Methods 158 6.3.8 Multi-agent
Methods 160 6.3.9 Other Methods 163 Acknowledgments 166 References 166 7
UAS Conflict Detection and Resolution Using Differential Geometry Concepts
175 Hyo-Sang Shin, Antonios Tsourdos and Brian White 7.1 Introduction 175
7.2 Differential Geometry Kinematics 177 7.3 Conflict Detection 178 7.3.1
Collision Kinematics 178 7.3.2 Collision Detection 180 7.4 Conflict
Resolution: Approach I 182 7.4.1 Collision Kinematics 183 7.4.2 Resolution
Guidance 186 7.4.3 Analysis and Extension 188 7.5 Conflict Resolution:
Approach II 191 7.5.1 Resolution Kinematics and Analysis 192 7.5.2
Resolution Guidance 193 7.6 CD&R Simulation 195 7.6.1 Simulation Results:
Approach I 195 7.6.2 Simulation Results: Approach II 199 7.7 Conclusions
200 References 203 8 Aircraft Separation Management Using Common
Information Network SAA 205 Richard Baumeister and Graham Spence 8.1
Introduction 205 8.2 CIN Sense and Avoid Requirements 208 8.3 Automated
Separation Management on a CIN 212 8.3.1 Elements of Automated Aircraft
Separation 212 8.3.2 Grid-Based Separation Automation 214 8.3.3
Genetic-Based Separation Automation 214 8.3.4 Emerging Systems-Based
Separation Automation 216 8.4 Smart Skies Implementation 217 8.4.1 Smart
Skies Background 217 8.4.2 Flight Test Assets 217 8.4.3 Communication
Architecture 219 8.4.4 Messaging System 221 8.4.5 Automated Separation
Implementation 223 8.4.6 Smart Skies Implementation Summary 223 8.5 Example
SAA on a CIN - Flight Test Results 224 8.6 Summary and Future Developments
229 Acknowledgments 231 References 231 Part IV SAA Applications 9 AgentFly:
Scalable, High-Fidelity Framework for Simulation, Planning and Collision
Avoidance of Multiple UAVs 235 David Sislak, Premysl Volf, Stepan Kopriva
and Michal Pechoucek 9.1 Agent-Based Architecture 236 9.1.1 UAV Agents 237
9.1.2 Environment Simulation Agents 237 9.1.3 Visio Agents 238 9.2 Airplane
Control Concept 238 9.3 Flight Trajectory Planner 241 9.4 Collision
Avoidance 245 9.4.1 Multi-layer Collision Avoidance Architecture 246 9.4.2
Cooperative Collision Avoidance 247 9.4.3 Non-cooperative Collision
Avoidance 250 9.5 Team Coordination 252 9.6 Scalable Simulation 256 9.7
Deployment to Fixed-Wing UAV 260 Acknowledgments 263 References 263 10 See
and Avoid Using Onboard Computer Vision 265 John Lai, Jason J. Ford, Luis
Mejias, Peter O'Shea and Rod Walker 10.1 Introduction 265 10.1.1 Background
265 10.1.2 Outline of the SAA Problem 265 10.2 State-of-the-Art 266 10.3
Visual-EO Airborne Collision Detection 268 10.3.1 Image Capture 268 10.3.2
Camera Model 269 10.4 Image Stabilization 269 10.4.1 Image Jitter 269
10.4.2 Jitter Compensation Techniques 270 10.5 Detection and Tracking 272
10.5.1 Two-Stage Detection Approach 272 10.5.2 Target Tracking 278 10.6
Target Dynamics and Avoidance Control 278 10.6.1 Estimation of Target
Bearing 278 10.6.2 Bearing-Based Avoidance Control 279 10.7 Hardware
Technology and Platform Integration 281 10.7.1 Target/Intruder Platforms
281 10.7.2 Camera Platforms 282 10.7.3 Sensor Pod 286 10.7.4 Real-Time
Image Processing 288 10.8 Flight Testing 289 10.8.1 Test Phase Results 290
10.9 Future Work 290 10.10 Conclusions 291 Acknowledgements 291 References
291 11 The Use of Low-Cost Mobile Radar Systems for Small UAS Sense and
Avoid 295 Michael Wilson 11.1 Introduction 295 11.2 The UAS Operating
Environment 297 11.2.1 Why Use a UAS? 297 11.2.2 Airspace and Radio
Carriage 297 11.2.3 See-and-Avoid 297 11.2.4 Midair Collisions 298 11.2.5
Summary 299 11.3 Sense and Avoid and Collision Avoidance 300 11.3.1 A
Layered Approach to Avoiding Collisions 300 11.3.2 SAA Technologies 300
11.3.3 The UA Operating Volume 303 11.3.4 Situation Awareness 304 11.3.5
Summary 304 11.4 Case Study: The Smart Skies Project 305 11.4.1
Introduction 305 11.4.2 Smart Skies Architecture 305 11.4.3 The Mobile
Aircraft Tracking System 307 11.4.4 The Airborne Systems Laboratory 310
11.4.5 The Flamingo UAS 311 11.4.6 Automated Dynamic Airspace Controller
311 11.4.7 Summary 312 11.5 Case Study: Flight Test Results 312 11.5.1
Radar Characterisation Experiments 312 11.5.2 Sense and Avoid Experiments
319 11.5.3 Automated Sense and Avoid 324 11.5.4 Dynamic Sense and Avoid
Experiments 326 11.5.5 Tracking a Variety of Aircraft 326 11.5.6 Weather
Monitoring 331 11.5.7 The Future 332 11.6 Conclusion 333 Acknowledgements
333 References 334 Epilogue 337 Index 339