| Introduction to this Book | p. 1 |
| How to Make a Robot Behave - Now and Then | p. 1 |
| Outlook | p. 3 |
| A Brief Introduction to Mobile Robotics | p. 5 |
| This Book Is Not About Mobile Robotics | p. 5 |
| What Is Mobile Robotics? | p. 5 |
| The Emergence of Behaviour | p. 9 |
| Examples of Research Issues in Autonomous Mobile Robotics | p. 12 |
| Summary | p. 13 |
| Introduction to Scientific Methods in Mobile Robotics | p. 15 |
| Introduction | p. 15 |
| Motivation For This Book: Analytical Robotics | p. 17 |
| Robot-Environment Interaction as Computation | p. 19 |
| A Theory of Robot-Environment Interaction | p. 21 |
| Robot Engineering vs. Robot Science | p. 23 |
| Scientific Method and Autonomous Mobile Robotics | p. 24 |
| Tools Used In This Book | p. 32 |
| Summary: The Contrast Between Experimental Mobile Robotics and Scientific Mobile Robotics | p. 33 |
| Statistical Tools for Describing Experimental Data | p. 35 |
| Introduction | p. 35 |
| The Normal Distribution | p. 36 |
| Parametric Methods to Compare Samples | p. 39 |
| Nonparametric Methods to Compare Samples | p. 53 |
| Testing for Randomness in a Sequence | p. 66 |
| Parametric Tests for a Trend (Correlation Analysis) | p. 68 |
| Nonparametric Tests for a Trend | p. 76 |
| Analysing Categorical Data | p. 81 |
| Principal Component Analysis | p. 92 |
| Exercises | p. 96 |
| Describing Behaviour Quantitatively Through Dynamical Systems Theory and Chaos Theory | p. 99 |
| Introduction | p. 99 |
| Dynamical Systems Theory | p. 99 |
| Describing (Robot) Behaviour Quantitatively Through Phase Space Analysis | p. 110 |
| Sensitivity to Initial Conditions: The Lyapunov Exponent | p. 114 |
| Aperiodicity: The Dimension of Attractors | p. 130 |
| Summary | p. 133 |
| Analysis of Agent Behaviour: Case Studies | p. 135 |
| Analysing the Movement of a Random-Walk Mobile Robot | p. 135 |
| "Chaos Walker" | p. 140 |
| Analysing the Flight Paths of Carrier Pigeons | p. 147 |
| Computer Modelling of Robot-Environment Interaction | p. 153 |
| Introduction | p. 153 |
| Some Practical Considerations Regarding Robot Modelling | p. 155 |
| Case Study: Model Acquisition Using Artificial Neural Networks | p. 158 |
| Linear Polynomial Models and Linear Recurrence Relations | p. 164 |
| ARMAX Modelling | p. 165 |
| NARMAX Modelling | p. 169 |
| Interpretation of Polynomial Models (Sensitivity Analysis) | p. 171 |
| Summary | p. 179 |
| Accurate Simulation Through System Identification | p. 181 |
| Introduction | p. 181 |
| Environment Modelling: ARMAX Example | p. 184 |
| Localisation Through Environment Modelling | p. 187 |
| Robot Programming Through System Identification | p. 199 |
| Identifying a Wall-Following Behaviour Using ARMAX | p. 199 |
| Identifying Wall-Following Behaviour Using NARMAX | p. 202 |
| Platform-Independent Programming Through Task Identification: The RobotMODIC Process | p. 204 |
| Obtaining Task-Achieving Competences Through Training | p. 206 |
| Behaviour to Code: Direct Translation of Observed Behaviour Into Robot Code | p. 211 |
| Other Applications of Transparent Modelling Through System Identification | p. 219 |
| Sensor Identification | p. 219 |
| Quantitative Comparison of Behaviours and Model Validity | p. 223 |
| Conclusion | p. 231 |
| Motivation for Scientific Methods in Robotics | p. 231 |
| Quantitative Descriptions of Robot-Environment Interaction | p. 232 |
| A Theory of Robot-Environment Interaction | p. 233 |
| Outlook: Towards Analytical Robotics | p. 235 |
| Answers to Exercises | p. 237 |
| References | p. 243 |
| Index | p. 249 |
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