Table Of Content

Durham E-Theses Autonomous, Collaborative, Unmanned Aerial Vehicles for Search and Rescue AMBROSE-THURMAN, ANDREW,MICHAEL,LUKE How to cite: AMBROSE-THURMAN, ANDREW,MICHAEL,LUKE (2014) Autonomous, Collaborative, Unmanned Aerial Vehicles for Search and Rescue, Durham theses, Durham University. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/10652/ Use policy ThisworkislicensedunderaCreativeCommonsAttribution2.0UK:England&Wales (CC BY) AcademicSupportO(cid:30)ce,DurhamUniversity,UniversityO(cid:30)ce,OldElvet,DurhamDH13HP e-mail: [email protected]: +4401913346107 http://etheses.dur.ac.uk Abstract Autonomous, Collaborative, Unmanned Aerial Vehicles for Search and Rescue Andrew Michael Luke Ambrose-Thurman SearchandRescueisavitallyimportantsubject,andonewhichcanbeimproved through the use of modern technology. This work presents a number of advances aimed towards the creation of a swarm of autonomous, collaborative, unmanned aerial vehicles for land-based search and rescue. The main advances are the devel- opment of a diffusion based search strategy for route planning, research into GPS (including the Durham Tracker Project and statistical research into altitude errors), and the creation of a relative positioning system (including discussion of the er- rors caused by fast-moving units). Overviews are also given of the current state of research into both UAVs and Search and Rescue. Autonomous, Collaborative, Unmanned Aerial Vehicles for Search and Rescue by Andrew Michael Luke Ambrose-Thurman Submitted in conformity with the requirements for the degree of Doctor of Philosophy School of Engineering and Computing Sciences University of Durham Copyright (cid:13)c 2014 Andrew Michael Luke Ambrose-Thurman Contents 1 Introduction 1 2 Search and Rescue 6 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Creating probability maps . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2.1 Calculating POD . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2.2 Calculating POA . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.3 Division of areas . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.4 Computer systems . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Searching probability maps . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.1 Current methods for human searchers . . . . . . . . . . . . . 22 2.3.2 Distributed systems . . . . . . . . . . . . . . . . . . . . . . . 22 2.3.3 Greedy lookahead algorithm . . . . . . . . . . . . . . . . . . . 23 3 Search and Rescue as a Weighted Cleaning Problem 25 3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.2.1 Diffusion methods . . . . . . . . . . . . . . . . . . . . . . . . 30 3.2.2 Neighbours . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.2.3 Computing power . . . . . . . . . . . . . . . . . . . . . . . . 41 3.2.4 Previous work. . . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.3 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.3.1 Cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.3.2 Perfect cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . 49 i ii CONTENTS 3.3.3 Imperfect Cleaning . . . . . . . . . . . . . . . . . . . . . . . . 49 3.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.4.1 Incomplete data sets . . . . . . . . . . . . . . . . . . . . . . . 51 3.4.2 Computational complexity . . . . . . . . . . . . . . . . . . . . 53 3.4.3 Perfect cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.4.4 Imperfect cleaning . . . . . . . . . . . . . . . . . . . . . . . . 55 3.4.5 Variable values . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.4.6 Comparison between map sets . . . . . . . . . . . . . . . . . 58 3.4.7 Comparison between methods . . . . . . . . . . . . . . . . . . 62 3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.6 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4 Unmanned Aerial Vehicles 70 4.1 Autonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.1.1 Control structure . . . . . . . . . . . . . . . . . . . . . . . . . 75 4.2 Other research groups . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2.1 STARMAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2.2 GRASP Lab . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.2.3 ETH Zurich Flying Machine Arena . . . . . . . . . . . . . . . 79 4.2.4 UltraSwarm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.5 DelFly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.6 Berkeley Aerobot . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.7 MAGICC Lab . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.2.8 MIT — RAVEN Lab . . . . . . . . . . . . . . . . . . . . . . . 82 4.2.9 Swarmanoid . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 4.2.10 ORCHID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.2.11 SUAAVE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.2.12 UAVTech . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.2.13 NASA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.2.14 QinetiQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.2.15 Other commercial groups . . . . . . . . . . . . . . . . . . . . 86 4.3 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 CONTENTS iii 4.3.1 Sensors for localisation . . . . . . . . . . . . . . . . . . . . . . 87 4.3.2 Sensors for task completion . . . . . . . . . . . . . . . . . . . 87 4.3.3 Sensor Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4.4 Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.5 UAVs in emergency situations . . . . . . . . . . . . . . . . . . . . . . 91 4.5.1 UAVs for Search and Rescue . . . . . . . . . . . . . . . . . . 93 5 GPS tracking 96 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.3 Durham Tracker Project . . . . . . . . . . . . . . . . . . . . . . . . . 101 5.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 5.3.2 Previous work. . . . . . . . . . . . . . . . . . . . . . . . . . . 106 5.4 Modifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 5.4.1 Reasons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 5.4.2 Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.4.3 Results from changes . . . . . . . . . . . . . . . . . . . . . . . 132 5.5 Comparison with commercial trackers . . . . . . . . . . . . . . . . . 136 5.5.1 Globalsat TR-102 . . . . . . . . . . . . . . . . . . . . . . . . 136 5.5.2 Smartphone GPS tracker software . . . . . . . . . . . . . . . 138 5.5.3 SPOT Personal Tracker . . . . . . . . . . . . . . . . . . . . . 140 5.5.4 Globalstar SmartONE . . . . . . . . . . . . . . . . . . . . . . 140 5.5.5 MeiTrack MVT-600 . . . . . . . . . . . . . . . . . . . . . . . 141 5.5.6 MeiTrack VT-400. . . . . . . . . . . . . . . . . . . . . . . . . 141 5.5.7 CelloTrack Solar . . . . . . . . . . . . . . . . . . . . . . . . . 141 5.5.8 ATrack AY5i . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 5.5.9 UAV trackers . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 5.5.10 Animal trackers . . . . . . . . . . . . . . . . . . . . . . . . . . 143 5.5.11 Online tracker servers . . . . . . . . . . . . . . . . . . . . . . 144 5.5.12 Comparisons with Durham tracker . . . . . . . . . . . . . . . 145 5.5.13 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 5.6 Future changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 iv CONTENTS 5.6.1 Balance check . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 5.6.2 Audio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 5.6.3 On-tracker user interface. . . . . . . . . . . . . . . . . . . . . 163 5.6.4 Memory card . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 5.6.5 Multi sockets . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 5.6.6 Real time commands . . . . . . . . . . . . . . . . . . . . . . . 166 5.6.7 Split files for data storage . . . . . . . . . . . . . . . . . . . . 166 5.6.8 File size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 5.6.9 Relative Positioning . . . . . . . . . . . . . . . . . . . . . . . 167 6 GPS Altitude Errors 168 6.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 6.2 Introduction to the problem . . . . . . . . . . . . . . . . . . . . . . . 169 6.3 OpenStreetMap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 6.4 Shuttle Radar Topography Mission . . . . . . . . . . . . . . . . . . . 172 6.5 Additional sources of error . . . . . . . . . . . . . . . . . . . . . . . . 172 6.5.1 Altimeters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 6.5.2 Lat/Long errors . . . . . . . . . . . . . . . . . . . . . . . . . 173 6.5.3 Additional height . . . . . . . . . . . . . . . . . . . . . . . . . 173 6.5.4 Insufficient resolution . . . . . . . . . . . . . . . . . . . . . . 174 6.5.5 Geoid adjustment . . . . . . . . . . . . . . . . . . . . . . . . 174 6.5.6 Dilution of Precision . . . . . . . . . . . . . . . . . . . . . . . 174 6.6 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 6.6.1 Comparison with barometric data . . . . . . . . . . . . . . . 179 6.6.2 Comparison with FAA data . . . . . . . . . . . . . . . . . . . 179 6.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 7 Relative Positioning 184 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 7.1.1 Connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 7.1.2 Signal strength . . . . . . . . . . . . . . . . . . . . . . . . . . 187 7.1.3 Interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 CONTENTS v 7.1.4 Angle of Arrival (AOA) . . . . . . . . . . . . . . . . . . . . . 189 7.1.5 Time Difference of Arrival (TDOA) . . . . . . . . . . . . . . 190 7.1.6 Time of Arrival (TOA) . . . . . . . . . . . . . . . . . . . . . 192 7.1.7 UAV localisation decision . . . . . . . . . . . . . . . . . . . . 193 7.2 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 7.2.1 Overviews of relative positioning . . . . . . . . . . . . . . . . 194 7.2.2 BeepBeep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 7.2.3 PinPoint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 7.3 Time of Arrival measurements. . . . . . . . . . . . . . . . . . . . . . 198 7.3.1 Pulse description . . . . . . . . . . . . . . . . . . . . . . . . . 200 7.3.2 Fast Chirp Transform . . . . . . . . . . . . . . . . . . . . . . 200 7.3.3 Fourier Transform and Cross Correlation . . . . . . . . . . . 207 7.4 Sources of error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 7.4.1 Clock resolution . . . . . . . . . . . . . . . . . . . . . . . . . 210 7.4.2 Clock Drift . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 7.5 Stationary Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . 213 7.5.1 Stationary Results . . . . . . . . . . . . . . . . . . . . . . . . 215 7.5.2 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 7.6 Movement errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 7.6.1 Negligible velocities . . . . . . . . . . . . . . . . . . . . . . . 220 7.6.2 Non-negligible velocities . . . . . . . . . . . . . . . . . . . . . 221 7.6.3 Distances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 7.6.4 Inertial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 7.6.5 Moving Results . . . . . . . . . . . . . . . . . . . . . . . . . . 224 7.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 8 Conclusion 242 8.1 Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 8.2 Closing remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 A Radio Distress Beacon 248 B Missing person types 250

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Aerial Vehicles for Search and Rescue, Durham theses, Durham University. Available at Durham School of Engineering and Computing Sciences known, as is the probability that they would be discovered if they were (POD), so the new POA can be worked out.[15]. Bayes theory states that. P(A | B)
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Aerial Vehicles for Search and Rescue, Durham theses, Durham University. Available at Durham School of Engineering and Computing Sciences known, as is the probability that they would be discovered if they were (POD), so the new POA can be worked out.[15]. Bayes theory states that. P(A | B)

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