Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery
Wiley-IEEE Press (Verlag)
978-1-119-87083-8 (ISBN)
Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery studies various elements of deployment of networks of unmanned aerial vehicle (UAV) base stations for providing communication to ground users in disaster areas, covering problems like ground traffic monitoring, surveillance of environmental disaster areas (e.g. brush fires), using UAVs in rescue missions, converting UAV video surveillance, and more. The work combines practical problems, implementable and computationally efficient algorithms to solve these problems, and mathematically rigorous proofs of each algorithm’s convergence and performance.
One such example provided by the authors is a novel biologically inspired motion camouflage algorithm to covert video surveillance of moving targets by an unmanned aerial vehicle (UAV). All autonomous navigation and deployment algorithms developed in the book are computationally efficient, easily implementable in engineering practice, and based only on limited information on other UAVs of each and the environment.
Sample topics discussed in the work include:
Deployment of UAV base stations for communication, especially with regards to maximizing coverage and minimizing interference
Deployment of UAVs for surveillance of ground areas and targets, including surveillance of both flat and uneven areas
Navigation of UAVs for surveillance of moving areas and targets, including disaster areas and ground traffic monitoring
Autonomous UAV navigation for covert video surveillance, offering extensive coverage of optimization-based navigation
Integration of UAVs and public transportation vehicles for parcel delivery, covering both one-way and round trips
Professionals in navigation and deployment of unmanned aerial vehicles, along with researchers, engineers, scientists in intersecting fields, can use Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery to gain general knowledge on the subject along with practical, precise, and proven algorithms that can be deployed in a myriad of practical situations.
HAILONG HUANG, PhD, is an Assistant Professor at The Hong Kong Polytechnic University, Hong Kong. He is also an Associate Editor for the International Journal of Advanced Robotic Systems. His research interests include multi-robot systems, coverage control; system modeling and simulation. ANDREY V. SAVKIN, PhD, is a Professor and Head of Systems and Control in the School of Electrical Engineering and Telecommunications at University of New South Wales, Sydney, Australia. He was a co-author of the Wiley title Decentralized Coverage Control Problems for Mobile Robotic Sensor and Actuator Networks (2015). CHAO HUANG, PhD, is a Research Assistant Professor at The Hong Kong Polytechnic University, Hong Kong. From July 2020 to May 2021, she acted as a Guest Editor for the Spectrum special issue on "Advanced Sensing and Control for Connected and Automated Vehicles".
Author Biographies ix
Preface xi
1 Introduction 1
1.1 Applications of UAVs 1
1.2 Problems of Autonomous Navigation and Deployment of UAVs 2
1.3 Overview and Organization of the Book 4
1.4 Some Other Remarks 5
References 6
2 Deployment of UAV Base Stations for Wireless Communication Coverage 11
2.1 Introduction 11
2.2 Related Work 14
2.3 UAV-BS Deployment for Maximizing Coverage 17
2.3.1 Problem Statement 17
2.3.2 Proposed Solution 19
2.3.3 Evaluation 21
2.4 UAV-BS Deployment for Maximizing Coverage and Minimizing Interference 24
2.4.1 System Model and Problem Statement 24
2.4.2 Proposed Solution 27
2.4.3 Simulation Results 31
2.4.3.1 Dataset and Simulation Set-Up 31
2.4.3.2 Comparing Approaches 32
2.4.3.3 Simulation Results 32
2.5 Voronoi Partitioning-Based UAV-BS Deployment 36
2.5.1 Problem Statement and Main Results 36
2.5.2 Simulation Results 41
2.6 Range-Based UAV-BS Deployment 43
2.6.1 Problem Statement and Main Results 43
2.6.2 Simulation Results 49
2.7 Summary 52
References 52
3 Deployment of UAVs for Surveillance of Ground Areas and Targets 57
3.1 Introduction 57
3.2 Related Work 60
3.3 Asymptotically Optimal UAV Deployment for Surveillance of a Flat Ground Area 61
3.3.1 Problem Statement 61
3.3.2 Deployment Algorithm 63
3.3.3 Evaluation 67
3.4 UAV Deployment for Surveillance of Uneven Ground Areas 71
3.4.1 Problem Statement 71
3.4.2 Deployment Algorithm 73
3.4.3 Evaluation 78
3.5 2D UAV Deployment for Ground Target Surveillance 80
3.5.1 Problem Statement 80
3.5.2 Proposed Solution 82
3.5.3 Evaluation 85
3.6 3D UAV Deployment for Ground Target Surveillance 87
3.6.1 Problem Statement 87
3.6.2 Proposed Solution 89
3.6.3 Evaluation 95
3.7 Summary and Future Research 99
References 100
4 Autonomous Navigation of UAVs for Surveillance of Ground Areas and Targets 105
4.1 Introduction 105
4.2 RelatedWork 108
4.3 Asymptotically Optimal Path Planning for Surveillance of Ground Areas 110
4.3.1 Problem Statement 110
4.3.2 Path Planning Algorithm 111
4.3.3 Simulation Results 114
4.4 Navigation of UAVs for Surveillance of a Moving Ground Area 117
4.4.1 Problem Statement 117
4.4.2 Navigation Law 119
4.4.2.1 Available Measurements 120
4.4.3 Simulation Results 122
4.5 Navigation of UAVs for Surveillance of Moving Targets on a Road Segment 125
4.5.1 Problem Statement 125
4.5.2 Proposal Solution 126
4.5.2.1 Monitoring Mode 126
4.5.2.2 Initial Mode 127
4.5.2.3 Searching Mode 128
4.5.2.4 Accumulating Mode 129
4.5.3 Simulation Results 130
4.6 Navigation of UAVs for Surveillance of Moving Targets along a Road 134
4.6.1 Problem Statement 134
4.6.2 Navigation Algorithm 137
4.6.3 Simulation Results 139
4.7 Navigation of UAVs for Surveillance of Groups of Moving Ground Targets 142
4.7.1 Problem Statement and Proposed Approach 143
4.7.2 Navigation Method 146
4.7.3 Simulation Results 150
4.8 Summary and Future Research 153
References 154
5 Autonomous UAV Navigation for Covert Video Surveillance 159
5.1 Introduction 159
5.2 Related Work 160
5.3 Optimization-Based Navigation 162
5.3.1 System Model 162
5.3.2 Problem Statement 165
5.3.3 Predictive DP Based Trajectory Planning Algorithm 166
5.3.3.1 Aeronautic Trajectory Refinement 169
5.3.4 Evaluation 174
5.4 Biologically Inspired Motion Camouflage-based Navigation 181
5.4.1 Problem Statement 182
5.4.1.1 Available Measurements 182
5.4.2 Motion Camouflage Guidance Law 183
5.4.3 Evaluation 185
5.5 Summary and Future Work 188
References 189
6 Integration of UAVs and Public Transportation Vehicles for Parcel Delivery 195
6.1 Introduction 195
6.2 Related Work 199
6.3 System Model 203
6.4 One-way Path Planning 204
6.4.1 Problem Statement 204
6.4.2 Proposed Solution 207
6.4.2.1 Path Traversal Time 207
6.4.2.2 Reliable Path Construction 210
6.4.2.3 Energy-aware Reliable Path 213
6.4.3 Evaluation 215
6.5 Round-trip Path Planning in a Deterministic Network 218
6.5.1 Deterministic Model 218
6.5.1.1 Extended Multimodal Network 220
6.5.2 Problem Statement 222
6.5.2.1 Shortest UAV Path Problem 222
6.5.3 Proposed Solution 223
6.5.3.1 The Dijkstra-based Algorithm 223
6.5.3.2 Reliable UAV Path 225
6.5.3.3 Extended Coverage 228
6.5.4 Evaluation 228
6.6 Round-trip Path Planning in a Stochastic Network 232
6.6.1 Problem Statement 233
6.6.2 Proposed Solution 235
6.6.2.1 Proposed Algorithm 235
6.6.2.2 Robust Round-trip Planning Algorithm 240
6.6.3 Evaluation 243
6.7 Summary and Future Work 246
References 246
Abbreviations 252
Index 253
| Erscheinungsdatum | 18.10.2022 |
|---|---|
| Sprache | englisch |
| Maße | 10 x 10 mm |
| Gewicht | 454 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Technik ► Fahrzeugbau / Schiffbau | |
| Technik ► Luft- / Raumfahrttechnik | |
| ISBN-10 | 1-119-87083-6 / 1119870836 |
| ISBN-13 | 978-1-119-87083-8 / 9781119870838 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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