Robot Ecology: Constraint-Based Design for Long-Duration Autonomy

by Magnus Egerstedt

Overview

A revolutionary new framework that draws on insights from ecology for the design and analysis of long-duration robots

Robots are increasingly leaving the confines of laboratories, warehouses, and manufacturing facilities, venturing into agriculture and other settings where they must operate in uncertain conditions over long timescales. This multidisciplinary book draws on the principles of ecology to show how robots can take full advantage of the environments they inhabit, including as sources of energy.

Magnus Egerstedt introduces a revolutionary new design paradigm—robot ecology—that makes it possible to achieve long-duration autonomy while avoiding catastrophic failures. Central to ecology is the idea that the richness of an organism’s behavior is a function of the environmental constraints imposed by its habitat. Moving beyond traditional strategies that focus on optimal policies for making robots achieve targeted tasks, Egerstedt explores how to use survivability constraints to produce both effective and provably safe robot behaviors. He blends discussions of ecological principles with the development of control barrier functions as a formal approach to constraint-based control design, and provides an in-depth look at the design of the SlothBot, a slow and energy-efficient robot used for environmental monitoring and conservation.

Visionary in scope, Robot Ecology presents a comprehensive and unified methodology for designing robots that can function over long durations in diverse natural environments.

Product Details

ISBN-13:	9780691230078
Publisher:	Princeton University Press
Publication date:	12/28/2021
Sold by:	Barnes & Noble
Format:	eBook
Pages:	360
File size:	49 MB
Note:	This product may take a few minutes to download.

About the Author

Magnus Egerstedt is the Stacey Nicholas Dean of Engineering in the Samueli School of Engineering at the University of California, Irvine. He is the coauthor of Graph Theoretic Methods in Multiagent Networks and Control Theoretic Splines: Optimal Control, Statistics, and Path Planning (both Princeton).

Table of Contents

Preface xiii

I Long-Duration Autonomy

1 Introduction 3

1.1 Long-Duration Autonomy 3

1.1.1 Lessons from Mars 4

1.1.2 Operations Beyond a Single Battery Charge 6

1.1.3 On the Value of Slowness 8

1.2 Survivability 10

1.2.1 Costs and Constraints 11

1.2.2 Robots that Do (Almost) Nothing 13

1.3 Coupling Between Environment and Robot 15

1.3.1 Ecosystems 16

1.3.2 Natural and Engineered Environments 17

1.4 Summarizing and Looking Ahead 18

2 Survival of the Robots 20

2.1 Behavior-Based Robotics 21

2.1.1 Behaviors in Robots and Animals 22

2.1.2 Arbitration Mechanisms 26

2.2 Multi-Robot Behaviors 31

2.2.1 Flocking and Swarming 31

2.2.2 Coordinated Control 33

2.2.3 Formation Control 37

2.2.4 Coverage Control 40

2.3 The Combinatorics of the Real World 43

2.3.1 Elephants Don't Ray Chess 43

2.3.2 Technology Readiness Levels 46

2.3.3 Constraints and Laws of Robotics 48

3 Ecological Connections 54

3.1 Organisms and Environments 56

3.1.1 Consumers and Resources 56

3.1.2 Niches and Fitness Sets 61

3.2 Interactions 66

3.2.1 Fecundity and Survival 66

3.2.2 Competition 68

3.2.3 Predators and Parasites 72

3.2.4 Social Behaviors 76

3.3 Ecologically Inspired Constraints 78

3.3.1 Ideal Free Distributions 79

3.3.2 Competitive and Cooperative Interactions 81

3.3.3 Thermoregulation and Task Persistification 85

3.3.4 Towards Robot Ecology 86

II Constraint-Based Control

4 Constraints and Barriers 91

4.1 Forward Invariance 92

4.1.1 Collision-Avoidance 92

4.1.2 Remaining Safe Forever 95

4.1.3 Nagumo and the Comparison Lemma 96

4.2 Control Barrier Functions 100

4.2.1 Optimization-Based Control 101

4.2.2 Further Considerations 104

4.2.3 Survivability Constraints 105

4.3 Collision-Avoidance 108

4.3.1 Centralized Safety Barriers 109

4.3.2 Decentralized Safety Barriers 112

4.4 Safe Learning 114

4.4.1 Learning Barrier Functions 118

4.4.2 Applications to Aerial Robotics 121

5 Persistification of Robotic Tasks 124

5.1 Energy Dynamics 125

5.1.1 Environmental Interactions 125

5.1.2 Task Persistification 130

5.2 Variations on the CBF Theme 133

5.2.1 High Relative Degree Barrier Functions 133

5.2.2 Time Varying Barrier Functions 137

5.2.3 Solving the Persistification Problem 138

5.3 Environmental Monitoring 139

5.3.1 Exploration 140

5.3.2 Coverage 143

6 Composition of Barrier Functions 148

6.1 Boolean Composition 149

6.1.1 Disjunctions and Conjunctions 149

6.1.2 Secondary Operations 151

6.2 Non-Smooth Barrier Functions 153

6.2.1 Generalized Gradients 155

6.2.2 Set-Valued Lie Derivatives 156

6.3 Min/Max Barrier Functions 159

6.3.1 Boolean Composition of Barrier Functions 161

6.3.2 Navigation Example 165

6.4 Connectivity-Preserving Coordinated Control 167

6.4.1 Composite Safety and Connectivity Barrier Functions 168

6.4.2 Maintaining Dynamic Connectivity Graphs 171

III Robots in the Wild

7 Robot Ecology 179

7.1 Constraints From Behavioral Ecology 181

7.1.1 Constituent Constraints 181

7.1.2 Survivability Constraints 187

7.2 Goal-Driven Behaviors 193

7.2.1 From Gradient Descent to Barrier-Based Descent 195

7.2.2 Costs as Constraints 199

7.2.3 Finite-Time Performance 202

7.3 Goal-Driven Multi-Robot Systems 204

7.3.1 Formation and Coverage Control Revisited 207

7.3.2 Sequential Composition of Behaviors 210

7.4 Putting it All Together 212

7.4.1 A Purposeful Yet Safe Expenditure of Energy 212

7.4.2 The End Game 218

8 Environmental Monitoring 221

8.1 Monitoring in Natural Environments 222

8.1.1 Biodiversity 223

8.1.2 Microclimates and Ecological Niche Models 227

8.1.3 Under the Tree Canopies 229

8.2 Wire-Traversing Robots 231

8.2.1 Design Considerations 232

8.2.2 Mechanical Design 235

8.3 The SlothBot 239

8.3.1 Motion Planning and Control 240

8.3.2 Long-Duration Deployment 243

9 Autonomy-on-Demand 248

9.1 Recruitable Robots 249

9.1.1 Task Specifications 249

9.1.2 Remote Access Control in the Robotarium 251

9.2 The Robotarium: An Autonomy-on-Demand Multi-Robot Platform 257

9.2.1 The Impetus Behind Remote-Access Robotics 257

9.2.2 Testbed Design 259

9.2.3 Safety and Robust Barrier Functions 263

9.3 Remote Experimentation 268

9.3.1 Submission Process 270

9.3.2 The Robotarium Userbase 272

9.3.3 User Experiments 277

9.3.4 Case Studies 279

Bibliography 287

Index 327

What People are Saying About This

From the Publisher

“I love this book and its novel and inspiring concept of robot ecology! It captures what both life and robot autonomy are all about, which is working towards our goals while ensuring survival. The book provides the framework to design robots that are well fitted to their environment and beautifully explains it with both mathematical rigor and intuition.”—Kristin Ytterstad Pettersen, Norwegian University of Science and Technology

“Grounded in decades of scholarship by the author, this book ties the notion of constraint-based optimization to concepts from ecology and biology to explore how we might design robotic systems for long-term autonomy in their environment.”—Nikolaus Correll, University of Colorado Boulder

“A significant contribution. This enjoyable book presents a philosophy of ‘robot ecology’ that is original and holistic in its approach. Egerstedt inspires us to think differently about robot deployment.”—Heiko Hamann, University of Lübeck