Autonomous Underwater Vehicles Design and practice

The recent development of advanced processing capabilities and higher yield power supplies means that Autonomous Underwater Vehicle (AUVs) are finding novel and increasingly advanced applications in research, military and commercial settings. This timely book provides a state-of-the-art overview of...

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Bibliographic Details
Main Author Ehlers, Frank
Format eBook
LanguageEnglish
Published Stevenage The Institution of Engineering and Technology 2020
Institution of Engineering & Technology
SciTech Publishing
Edition1
SeriesElectromagnetics and Radar
Subjects
Marine & Naval
Marine engineering
TECHNOLOGY & ENGINEERING
mobile robots
telerobotics
autonomous underwater vehicles
marine robots
marine navigation
marine control
Online AccessGet full text
ISBN9781785617034
1785617036
DOI10.1049/SBRA525E

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Table of Contents:
  • Chapter 1: Introduction -- Part I: Control -- Chapter 2: Sensor-based motion control of autonomous underwater vehicles, part I: modeling and low-complexity state estimation -- Chapter 3: Sensor-based motion control of autonomous underwater vehicles, part II: robust motion control strategies -- Chapter 4: Adaptive–robust control of autonomous underwater vehicle with unknown system dynamics -- -- Part II: Navigation -- Chapter 5: AUV navigation: challenges and solutions -- Chapter 6: Ultra-endurance AUVs: energy requirements and terrain-aided navigation -- Chapter 7: A simplified version of SLAM: data compression and data association for common UUV missions -- -- Part III: Toolset -- Chapter 8: Toolchain for autonomous systems and its use in real-life scenarios: from science to defence -- Chapter 9: Telemetry for AUVs -- Chapter 10: Pressure-tolerant and pressure-neutral systems for AUV -- -- Part IV: Cooperation -- Chapter 11: Optimization of waterspace management and scheduling for multiple unmanned vehicles -- Chapter 12: MONSUN: a swarm AUV for environmental monitoring and inspection -- Chapter 13: Reconfigurable, adaptable, multi-modality, mobile, wireless, energy-efficient, underwater sensor network of hover-capable AUVs -- -- Part V: Methodology -- Chapter 14: Task specification and behavior verification for UUV behavior design -- Chapter 15: Advanced AUV fault management -- Chapter 16: Designing, building and testing a fleet of novel AUV under the elevated requirements of an XPRIZE competition -- -- Part VI: Application -- Chapter 17: AUV navigation, guidance, and control for geoseismic data acquisition -- Chapter 18: Adaptive sampling and energy-efficient navigation in time-varying flows -- Chapter 19: Summary, conclusions, and future work --
  • Intro -- Contents -- About the editor -- Foreword -- List of authors -- 1. Introduction | Frank Ehlers -- 1.1 Robotics and the maritime environment -- 1.1.1 The roboticist's view -- 1.1.2 The statistical signal processing view -- 1.1.3 The system-of-systems view -- 1.2 Autonomy, or why the interplay between design and practice is so important -- 1.3 The organization of this book: from design to practice - there and back again -- Part I: Control -- 2. Sensor-based motion control of autonomous underwater vehicles, Part I: modeling and low-complexity state estimation | George C. Karras, Charalampos P. Bechlioulis, Panos Marantos, Shahab Heshmati-alamdari and Kostas J. Kyriakopoulos -- 2.1 Introduction -- 2.2 Underwater vehicle kinematics and dynamics -- 2.2.1 General representation -- 2.2.2 Modeling and online parameter identification example: 4-DoF underwater vehicle -- 2.3 State estimation for underwater vehicles -- 2.3.1 Introduction to CFs -- 2.3.2 CF design -- 2.4 Results -- 2.4.1 State estimation results -- 2.4.2 Online parameter identification results -- 2.5 Summary -- References -- 3. Sensor-based motion control of autonomous underwater vehicles, Part II: robust motion control strategies | Charalampos P. Bechlioulis, Shahab Heshmati-Alamdari, George C. Karras, Panos Marantos and Kostas J. Kyriakopoulos -- 3.1 Introduction -- 3.2 MPC for underwater vehicles -- 3.2.1 Preliminaries and problem formulation -- 3.2.2 Methodology -- 3.2.3 Experimental results -- 3.3 Model-free control for underwater vehicles -- 3.3.1 Fully actuated underwater vehicles -- 3.3.2 Underactuated underwater vehicles: Case I -- 3.3.3 Underactuated underwater vehicles: Case II -- 3.4 Summary -- References -- 4. Adaptive-robust control of autonomous underwater vehicle with unknown system dynamics | Spandan Roy, Sayan Basu Roy and Indra Narayan Kar
  • 11.3.2 Fuel limitation and charging constraints -- 11.3.3 Goal and capability constraints -- 11.3.4 Time dependency and wait constraints -- 11.3.5 Transit and transport constraints -- 11.3.6 Survey constraints -- 11.3.7 Additional post-survey task execution constraints -- 11.3.8 Cost function -- 11.4 Robust scheduling extensions -- 11.5 Simulation results -- 11.5.1 End-to-end mission scheduling -- 11.5.2 Deterministic and robust scheduling results -- 11.5.3 Computational tractability and constraint violations -- 11.6 Conclusions -- References -- 12. MONSUN: a swarm AUV for environmental monitoring and inspection | Erik Maehle, Benjamin Meyer, Cedric Isokeit and Ulrich Behrje -- 12.1 Introduction -- 12.2 Motivation and related work -- 12.2.1 Micro AUV swarms for monitoring and inspection -- 12.2.2 Related work on micro AUVs -- 12.3 The Monsun micro AUV -- 12.3.1 Design concept -- 12.3.2 Hardware -- 12.3.3 Software -- 12.3.4 Expansion set -- 12.4 Swarm behaviours -- 12.4.1 Localization and communication concept -- 12.4.2 Communication principles for swarm operations -- 12.5 Experiments -- 12.5.1 Clockwork Ocean -- 12.5.2 V-formation -- 12.6 Conclusions and future work -- Acknowledgements -- References -- 13. Reconfigurable, adaptable, multi-modality, mobile, wireless, energy-efficient, underwater sensor network of hover-capable AUVs | Vladimir Djapic -- 13.1 Micro AUVs -- 13.2 AUV communication and PNT -- 13.2.1 Nano modem, sea modem, and CSAC -- 13.2.2 Acoustic communications with JANUS -- 13.2.3 Ambient field clock synchronization -- 13.2.4 Acoustic synchronization and ranging estimation -- 13.2.5 Spiral beacon technology -- 13.3 AUV navigation -- 13.3.1 AUV navigation sensors -- 13.4 Acoustic navigation -- 13.5 Multi-robot coordination -- 13.6 Underwater SLAM and geophysical navigation -- 13.7 Detection potential of multiple AUV sensor network
  • 4.1 Background and motivation -- 4.1.1 Contributions -- 4.1.2 Organization and notations -- 4.2 The AUV dynamics and problem formulation -- 4.2.1 Brief dynamics of AUV -- 4.2.2 Problem formulation -- 4.3 Controller design -- 4.4 Stability analysis of ASRC -- 4.5 Simulation results -- 4.5.1 Results and discussions for Scenario 1 -- 4.5.2 Results and discussions for Scenario 2 -- 4.6 Conclusion and future direction -- References -- Part II: Navigation -- 5. AUV navigation: challenges and solutions | Kjetil Bergh Ånonsen, Kenneth Gade and Ove Kent Hagen -- 5.1 Introduction -- 5.1.1 Why is underwater navigation challenging? -- 5.1.2 Autonomous navigation -- 5.1.3 Chapter outline -- 5.2 Notation -- 5.3 INS fundamentals -- 5.3.1 Inertial sensors -- 5.3.2 Inertial navigation -- 5.3.3 AINS - core AUV aiding sensors -- 5.4 Properties of an AINS for an AUV -- 5.4.1 Estimation of orientation in general -- 5.4.2 Heading accuracy -- 5.4.3 Accuracy in roll/pitch -- 5.4.4 Accuracy in velocity -- 5.4.5 Accuracy in position -- 5.5 Additional aiding techniques -- 5.5.1 Magnetometer -- 5.5.2 Surface vessel to AUV aiding -- 5.5.3 Transponder positioning -- 5.5.4 Delta-position aiding -- 5.5.5 Geophysical navigation -- 5.5.6 Classification of SLAM methods for AUVs -- 5.6 Conclusions -- References -- 6. Ultra-endurance AUVs: energy requirements and terrain-aided navigation | Georgios Salavasidis, Andrea Munafò, Davide Fenucci, Catherine A. Harris, Thomas Prampart, Robert Templeton, Micheal Smart, Daniel T. Roper, Miles Pebody, Stephen D. McPhail, Eric Rogers and Alexander B. Phillips -- 6.1 Introduction -- 6.2 ALR1500 and ALR6000: two ultra-endurance AUVs -- 6.2.1 Mechanical construction and propulsion -- 6.2.2 On-board control and autonomy systems -- 6.2.3 Navigation sensor suite and science payload -- 6.3 Energy balance for long-range operations
  • 6.3.1 Battery and maximising energy storage -- 6.3.2 Propulsion power -- 6.3.3 Hotel load -- 6.3.4 Passive buoyancy management -- 6.3.5 Range and endurance calculation -- 6.4 TAN for ultra-endurance AUVs -- 6.4.1 Process model -- 6.4.2 Observation model -- 6.4.3 Rao-Blackwellised PF -- 6.4.4 RBPF point estimates -- 6.4.5 RBPF initialisation -- 6.4.6 RBPF simplification -- 6.4.7 RBPF algorithm -- 6.5 Long-range TAN using WR velocity -- 6.5.1 ALR6000 operations in the Southern Ocean -- 6.5.2 DR navigation -- 6.5.3 TAN set-up -- 6.5.4 Long-range TAN results -- 6.6 Crossing the Arctic Ocean with ALR1500 -- 6.6.1 Simulation environment of the Arctic Ocean -- 6.6.2 Arctic crossing navigation results -- 6.7 Conclusion and future work -- Acknowledgements -- References -- 7. A simplified version of SLAM: data compression and data association for common UUV missions | Ashwin Sarma -- 7.1 Introduction -- 7.2 Development of MLE and relation to Kalman update -- 7.2.1 MLE development -- 7.2.2 VOG-SLAM Kalman update -- 7.3 Sonar data processing and measurement generation -- 7.3.1 Detector -- 7.3.2 Connected component clustering and labeling -- 7.3.3 Mapping detections to UTM frame -- 7.3.4 UTM uncertainty region associated with each cluster -- 7.3.5 SLAM measurement and error covariance generation -- 7.4 Data association to determine persistent features -- 7.5 Performance example -- 7.6 Conclusions and future work -- References -- Part III: Toolset -- 8. Toolchain for autonomous systems and its use in real-life scenarios: from science to defence | Paulo Sousa Dias, José Pinto and João Borges Sousa -- 8.1 Introduction -- 8.2 The toolchain -- 8.2.1 Communication -- 8.2.2 DUNE - on-board control software -- 8.2.3 Extensions to the toolchain -- 8.2.4 Neptus - command and control framework -- 8.3 Ripples -- 8.4 Applying the toolchain -- 8.4.1 Mine countermeasures
  • 8.4.2 Digital acoustic communications in submarine distress -- 8.4.3 Multi-robot coastal oceanography -- 8.4.4 Large-scale open ocean exploration -- 8.5 Integration with other frameworks -- 8.6 Conclusion -- References -- 9. Telemetry for AUVs | João Alves, Konstantinos Pelekanakis and Roberto Petroccia -- 9.1 Introduction -- 9.1.1 The requirement for telemetry -- 9.2 Underwater communications modalities -- 9.2.1 Underwater optical communications -- 9.2.2 Underwater RF communications -- 9.2.3 UWA communications -- 9.2.4 Modalities recap -- 9.3 Physical layer -- 9.3.1 Non-coherent systems -- 9.3.2 Coherent systems -- 9.4 Underwater networking -- 9.4.1 Data link layer -- 9.4.2 Network layer -- 9.4.3 Cognitive communications -- 9.5 Security in underwater communications -- 9.6 Interoperability and standards -- 9.7 Future trends -- References -- 10. Pressure-tolerant and pressure-neutral systems for AUV | Gunnar Brink and Gerhard Körner -- 10.1 Basic design of pressure-neutral systems -- 10.1.1 Mechanical construction -- 10.1.2 Casting systems -- 10.2 Pressure-neutral electrical and electronic assemblies -- 10.2.1 Suitable components -- 10.2.2 Optical systems and displays -- 10.3 Pressure-neutral power supplies and battery systems -- 10.3.1 Battery systems -- 10.4 Pressure-neutral drives -- 10.4.1 Submersible motors and drives -- 10.5 Elastic buoyancy foams in pressure-neutral technology -- 10.5.1 Recap and outlook -- Uncited references -- References -- Part IV: Cooperation -- 11. Optimization of waterspace management and scheduling for multiple unmanned vehicles | Matthew J. Bays and Thomas A. Wettergren -- 11.1 Introduction -- 11.1.1 Related work -- 11.1.2 Overview of the chapter -- 11.2 Multiple UUV logistics scheduling using MILP -- 11.3 Constraint formulation -- 11.3.1 Docking and deployment constraints
  • 13.8 Example: modular micro AUVs and communication