Contemporary Planetary Robotics An Approach Toward Autonomous Systems

For readers from both academia and industry wishing to pursue their studies and /or careers in planetary robotics, this book represents a one-stop tour of the history, evolution, key systems, and technologies of this emerging field.

The book provides a comprehensive introduction to the key techniques and technologies that help to achieve autonomous space systems for cost-effective, high performing planetary robotic missions. Main topics covered include robotic vision, surface navigation, manipulation, mission operations and autonomy, being explained in
both theoretical principles and practical use cases.

The book recognizes the importance of system design hence discusses practices and tools that help take mission concepts to baseline design solutions, making it a practical piece of scientific reference suited to a variety of practitioners in planetary robotics.

Yang Gao, FIET FRAeS, is the Professor of Space Autonomous Systems within Surrey Space Centre at the University of Surrey, United Kingdom. She heads the Surrey Technology for Autonomous Systems and Robotics (STAR) Lab that specialises in autonomy & modeling, visual navigation, modern control theories, robot soil interaction and biomimetic mechanisms with applications to spacecraft and robots alike. She brings over sixteen years of R&D experience in solving robotic system problems, in which she have been a Principle Investigator of internationally teamed projects funded by European and UK research funding bodies as well as commercial companies. Prof. Gao is also actively involved in real world space mission development and championing the Surrey Low-cost Space Engineering Approach within missions like ExoMars, Proba3, LM1, LPSR, CABLE, MoonLITE, and Moonraker.

List of Contributors XIII

1 Introduction 1
Yang Gao, Elie Allouis, Peter Iles, Gerhard Paar, and José de Gea Fernández

1.1 Evolution of Extraterrestrial Exploration and Robotics 1

1.2 Planetary Robotics Overview 4

1.3 Scope and Organization of the Book 6

1.4 Acknowledgments 9

2 Planetary Robotic System Design 11
Elie Allouis and Yang Gao

2.1 Introduction 11

2.2 A System Design Approach: From Mission Concept to Baseline Design 12

2.2.1 Mission Scenario Definition 14

2.2.2 Functional Analysis 14

2.2.3 Requirements Definition and Review 15

2.2.4 Design Drivers Identification 17

2.2.5 Concept Evaluation and Trade-Off 17

2.3 Mission Scenarios: Past, Current, and Future 19

2.3.1 Lander Missions 19

2.3.1.1 Luna Sample-Return Landers 20

2.3.1.2 Viking Landers 21

2.3.1.3 Mars Surveyor Lander Family and Successors 23

2.3.1.4 Huygens Lander 25

2.3.1.5 Beagle 2 Lander 28

2.3.1.6 Philae Lander 29

2.3.2 Rover Missions 30

2.3.2.1 Lunokhod 1 and 2 Rovers 31

2.3.2.2 Prop-M Rover 33

2.3.2.3 Sojourner Rover 34

2.3.2.4 Spirit and Opportunity Rovers 36

2.3.2.5 Curiosity Rover 39

2.3.2.6 Chang’E 3 Rover 42

2.3.2.7 ExoMars Rover 43

2.3.2.8 Mars 2020 Rover 46

2.3.3 Future Mission Concepts 46

2.3.3.1 Toward New Business Models 46

2.3.3.2 Medium-Term Mission Concepts 47

2.3.3.3 Long-Term Mission Ideas 47

2.4 Environment-Driven Design Considerations 47

2.4.1 Gravity 49

2.4.2 Temperature 49

2.4.3 Atmosphere and Vacuum 51

2.4.4 Orbital Characteristics 52

2.4.4.1 Distance to the Sun 53

2.4.4.2 Length of Days 53

2.4.5 Surface Conditions 54

2.4.5.1 Rocks 54

2.4.5.2 Dusts 55

2.4.5.3 Liquid 56

2.4.6 Properties of Planetary Bodies and Moons 56

2.5 Systems Design Drivers and Trade-Offs 56

2.5.1 Mission-Driven System Design Drivers 58

2.5.1.1 Mass 59

2.5.1.2 Target Environment 59

2.5.1.3 Launch Environment 59

2.5.1.4 Surface Deployment 60

2.5.1.5 Surface Operations 63

2.5.2 System Design Trade-Offs: A Case Study 63

2.5.2.1 Mission Scenario Definition: MSR/SFR 63

2.5.2.2 SFR System Design Drivers 64

2.5.2.3 SFR Subsystem Design Drivers 65

2.5.2.4 SFR Design Evaluation 68

2.6 System Operation Options 72

2.6.1 Operation Sequence 72

2.6.2 Operational Autonomy 75

2.6.2.1 Autonomous Functions 76

2.6.2.2 Autonomy Levels: Teleoperation versus Onboard Autonomy 77

2.7 Subsystem Design Options 79

2.7.1 Power Subsystem 79

2.7.1.1 Power Generation 80

2.7.1.2 Power Storage 84

2.7.2 Thermal Subsystem 90

2.7.2.1 SizingWarm/Cold Cases 92

2.7.2.2 Heat Provision 92

2.7.2.3 Heat Management (Transport and Dissipation) 94

2.7.2.4 Trade-Off Options 96

References 96

3 Vision and Image Processing 105
Gerhard Paar, Robert G. Deen, Jan-Peter Muller, Nuno Silva, Peter Iles, Affan Shaukat, and Yang Gao

3.1 Introduction 105

3.2 Scope of Vision Processing 108

3.2.1 Onboard Requirements 110

3.2.2 Mapping by Vision Sensors: Stereo as Core 112

3.2.3 Physical Environment 113

3.3 Vision Sensors and Sensing 114

3.3.1 Passive Optical Vision Sensors 116

3.3.2 Active Vision Sensing Strategies 117

3.3.3 Dedicated Navigation Vision Sensors: Example Exomars 118

3.3.3.1 Navigation (Perception/Stereo Vision) 119

3.3.3.2 Visual Localization and Slippage Estimation 119

3.3.3.3 Absolute Localization 120

3.4 Vision Sensors Calibration 120

3.4.1 Geometric Calibration 121

3.4.2 Radiometric Calibration 124

3.4.3 The Influence of Errors 125

3.5 Ground-Based Vision Processing 128

3.5.1 Compression and Decompression 129

3.5.2 3D Mapping 129

3.5.3 Offline Localization 133

3.5.4 Visualization and Simulation 135

3.6 Onboard Vision Processing 138

3.6.1 Preprocessing 138

3.6.2 Compression Modes 138

3.6.3 Stereo Perception Software Chain 139

3.6.4 Visual Odometry 140

3.6.5 Autonomous Navigation 141

3.7 Past and Existing Mission Approaches 142

3.7.1 Lunar Vision: Landers and Rovers 142

3.7.2 Viking Vision System 143

3.7.3 Pathfinder Vision Processing 144

3.7.4 MER and MSL Ground Vision Processing Chain 145

3.7.5 ExoMars Onboard Vision-Based Control Chain 150

3.7.6 ExoMars Onboard Vision Testing and Verification 151

3.7.7 ExoMars PanCam Ground Processing 152

3.7.8 Additional Robotic Vision Systems 155

3.8 Advanced Concepts 157

3.8.1 Planetary Saliency Models 157

3.8.2 Vision-Based Rover Sinkage Detection for Soil Characterization 162

3.8.3 Science Autonomy 166

3.8.4 Sensor Fusion 166

3.8.5 Artificial Intelligence and Cybernetics Vision 169

References 170

4 Surface Navigation 181
Peter Iles, Matthias Winter, Nuno Silva, Abhinav Bajpai, Yang Gao, Jan-Peter Muller, and Frank Kirchner

4.1 Introduction 181

4.2 Context 181

4.2.1 Definitions 182

4.2.2 Navigating on ExtraterrestrialWorlds 182

4.2.3 Navigation Systems on Current and Past Flight Rovers 183

4.2.3.1 Lunokhod I and II 183

4.2.3.2 Apollo Lunar Roving Vehicle 184

4.2.3.3 Sojourner Microrover 184

4.2.3.4 Mars Exploration Rovers 185

4.2.3.5 Mars Science Laboratory/Curiosity 188

4.2.3.6 Yutu/Jade Rabbit 190

4.3 Designing a Navigation System 190

4.3.1 Requirements 191

4.3.1.1 Performance Requirements 191

4.3.1.2 Environmental Requirements 192

4.3.1.3 Resource Requirements 193

4.3.1.4 Other Requirements 193

4.3.2 Design Considerations 194

4.3.2.1 Functional Components 194

4.3.2.2 Sensors 194

4.3.2.3 Software 196

4.3.2.4 Computational Resources 198

4.3.2.5 Rover Control Strategy 199

4.4 Localization Technologies and Systems 201

4.4.1 Orientation Estimation 201

4.4.1.1 Sun Finding 202

4.4.1.2 Star Trackers 203

4.4.1.3 Inertial Measurement Units 203

4.4.1.4 Vision Techniques 204

4.4.1.5 Antenna Null-Signal Technique 204

4.4.2 Relative Localization 205

4.4.2.1 Wheel Odometry 205

4.4.2.2 Visual Odometry 205

4.4.2.3 Other Vision-based Techniques 208

4.4.2.4 3D Visual Odometry 208

4.4.2.5 Speed Sensing 208

4.4.3 Absolute Localization 209

4.4.3.1 Rover-to-Orbiter Imagery Matching 209

4.4.3.2 Rover-to-Orbiter Horizon Matching 211

4.4.3.3 Rover-to-Orbiter Digital Elevation Model Matching 211

4.4.3.4 Orbiting Asset- or Earth-based Localization 212

4.4.3.5 Fixed Assets/Beacons Localization 213

4.4.3.6 Celestial Localization 214

4.4.4 Combining Localization Sources 214

4.4.4.1 Gaussian Filters 215

4.4.4.2 Particle Filters 216

4.4.4.3 Simultaneous Localization and Mapping 216

4.4.5 Example Systems 218

4.5 Autonomous Navigation 219

4.5.1 Sensing 219

4.5.2 Mapping 220

4.5.3 Terrain Assessment 222

4.5.4 Path Planning 223

4.5.4.1 Local Path Planning and Obstacle Avoidance 224

4.5.4.2 Global Path Planning 225

4.5.5 Control 227

4.6 Future of Planetary Surface Navigation 228

4.6.1 Planned Flight Rovers 228

4.6.1.1 ExoMars Rover 229

4.6.1.2 Mars 2020 Rover 233

4.6.2 Future Rover Missions 234

4.6.2.1 Mars Precision Lander 234

4.6.2.2 Resource Prospector Mission 234

4.6.3 Field Trials as Proving Grounds for Future Navigation Technologies 235

4.6.3.1 RESOLVE/Resource Prospector Mission (NASA/CSA) 236

4.6.3.2 SEEKER and SAFER (ESA) 239

4.6.3.3 Teleoperation Robotic Testbed (CSA) 240

4.6.3.4 Other Field Trials 241

4.6.4 Future Capabilities 242

4.6.4.1 SLAM Systems 242

4.6.4.2 Cooperative Robotics and New Mobility Concepts 242

4.6.4.3 Enhanced Processing Capabilities 244

4.6.4.4 New Sensors 244

4.6.4.5 New Applications of Orbital Imagery 245

References 247

5 Manipulation and Control 255
José de Gea Fernández, Elie Allouis, Karol Seweryn, Frank Kirchner, and Yang Gao

5.1 Introduction 255

5.1.1 Review of Planetary Robotic Arms 255

5.1.1.1 Mars Surveyor ’98/’01 256

5.1.1.2 Phoenix 258

5.1.1.3 MARS Exploration Rovers (MERs) 259

5.1.1.4 Beagle 2 260

5.1.1.5 Mars Science Laboratory 261

5.2 Robotic Arm System Design 263

5.2.1 Specifications and Requirements 263

5.2.1.1 Performance Requirements 264

5.2.1.2 Design Specifications 264

5.2.1.3 Environmental Design Considerations 267

5.2.2 Design Trade-Offs 268

5.2.2.1 Arm Kinematics 268

5.2.2.2 Structure and Material 269

5.2.2.3 Sensors 269

5.3 Robotic Arm Control 270

5.3.1 Low-Level Control Strategies 271

5.3.1.1 Position Control 271

5.3.1.2 Force Control 273

5.3.1.3 Dynamic Control 278

5.3.1.4 Visual Servoing 283

5.3.2 Manipulator Trajectory Generation 284

5.3.2.1 Trajectory Interpolation 285

5.3.2.2 On-Line Trajectory Generation 286

5.3.3 Collision Avoidance 287

5.3.3.1 Self-Collision Avoidance 288

5.3.4 High-Level Control Strategies 289

5.3.4.1 Path Planning 289

5.3.4.2 Telemanipulation 290

5.3.4.3 Higher Autonomy (E2–E4) 293

5.4 Testing and Validation 294

5.4.1 Testing Strategies 295

5.4.2 Scope of Testing Activities 297

5.4.2.1 Kinematic Calibration 298

5.4.2.2 Beyond Calibration 299

5.4.3 Validation Methods 299

5.4.3.1 Use of ABTs 301

5.5 Future Trends 304

5.5.1 Dual-Arm Manipulation 304

5.5.2 Whole-Body Motion Control 306

5.5.3 Mobile Manipulation 309

5.5.3.1 Mobile Manipulators as Research Platforms 309

5.5.3.2 DARPA Robotics Challenge (DRC) 310

5.5.3.3 Mobile Manipulators for Space 311

References 313

6 Mission Operations and Autonomy 321
Yang Gao, Guy Burroughes, Jorge Ocón, Simone Fratini, Nicola Policella, and Alessandro Donati

6.1 Introduction 321

6.2 Context 323

6.2.1 Mission Operation Concepts 323

6.2.2 Mission Operation Procedures 326

6.2.3 Onboard Segment Operation Modes 329

6.3 Mission Operation Software 330

6.3.1 Design Considerations 331

6.3.2 Ground Operation Software 332

6.3.3 Onboard Operation Software 336

6.3.4 Performance Measures 341

6.4 Planning and Scheduling (P&S) 343

6.4.1 P&S Software Design Considerations 343

6.4.2 Basic Principles & Techniques 343

6.4.2.1 Classical Methods 344

6.4.2.2 Neoclassical Methods 344

6.4.2.3 Solving Strategies 346

6.4.2.4 Temporal Planning 347

6.4.2.5 Scheduling 350

6.4.2.6 Handling Uncertainties 350

6.4.2.7 Planning Languages 351

6.4.3 P&S Software Systems 354

6.4.4 P&S Software Development Frameworks 357

6.5 Reconfigurable Autonomy 362

6.5.1 Rationale 362

6.5.2 State-of-the-Art Methods 363

6.5.3 Taxonomy 365

6.5.4 Design Examples: Reconfigurable Rover GNC 367

6.5.4.1 Application Layer 369

6.5.4.2 Reconfiguration Layer 370

6.5.4.3 Housekeeping Layer 372

6.5.4.4 Ontology Design 372

6.5.4.5 Rational Agent Design 374

6.5.4.6 Impact on Mission Operations 376

6.6 Validation and Verification 377

6.6.1 Simulation Tools 379

6.6.2 Model Checking 381

6.6.3 Ontology-based System Models 383

6.7 Case Study: Mars Rovers’ Goal-Oriented Autonomous Operation 384

6.7.1 Design Objectives 385

6.7.2 Onboard Software Architecture 385

6.7.3 Implementation and Validation 388

6.7.4 Integration with Ground Operation 392

6.7.5 Design Remarks 394

6.8 Future Trends 394

6.8.1 Autonomic Robotics 395

6.8.2 Common Robot Operating System 395

6.8.3 MultiAgent Systems 396

References 396

Index 403

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