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Computational Principles of Mobile Robotics, Second Edition

Book Description

This textbook for advanced undergraduates and graduate students emphasizes algorithms for a range of strategies for locomotion, sensing, and reasoning. It concentrates on wheeled and legged mobile robots but discusses a variety of other propulsion systems. The new edition includes advances in robotics and intelligent machines over the last ten years, including significant coverage of SLAM (simultaneous localization and mapping) and multi-robot systems. It includes additional mathematical background and an extensive list of sample problems. Various mathematical techniques that were assumed in the first edition are now briefly introduced in appendices at the end of the text to make the book more self-contained. Researchers as well as students in the field of mobile robotics will appreciate this comprehensive treatment of state-of-the-art methods and key technologies.

Table of Contents

  1. Coverpage
  2. Computational Principles of Mobile Robotics
  3. Title page
  4. Copyright page
  5. Dedication
  6. Contents
  7. Acknowledgments
  8. Preface to the Second Edition
  9. 1 Overview and Motivation
    1. 1.1 From Mechanisms to Computation
    2. 1.2 Historical Context
    3. 1.3 Biological Inspiration
    4. 1.4 Operational Regimes
    5. 1.5 Operational Modes
    6. 1.6 A Guide to This Book
    7. 1.7 Further Reading
    8. 1.8 Problems
  10. 2 Fundamental Problems
    1. 2.1 Path Planning for a Point Robot
    2. 2.2 Localization for a Point Robot
    3. 2.3 Sensing for a Point Robot
    4. 2.4 Mapping for a Point Robot
    5. 2.5 SLAM for a Point Robot
    6. 2.6 Looking Forward
    7. 2.7 Further Reading
    8. 2.8 Problems
  11. Part One: Locomotion and Perception
    1. 3 Mobile Robot Hardware
      1. 3.1 Locomotion
      2. 3.2 Off-Board Communication
      3. 3.3 Processing
      4. 3.4 Further Reading
      5. 3.5 Problems
    2. 4 Non-Visual Sensors and Algorithms
      1. 4.1 Basic Concepts
      2. 4.2 Contact Sensors: Bumpers
      3. 4.3 Inertial Sensors
      4. 4.4 Infrared Sensors
      5. 4.5 Sonar
      6. 4.6 Radar
      7. 4.7 Laser Rangefinders
      8. 4.8 Satellite-Based Positioning
      9. 4.9 Data Fusion
      10. 4.10 Biological Sensing
      11. 4.11 Further Reading
      12. 4.12 Problems
    3. 5 Visual Sensors and Algorithms
      1. 5.1 Visual Sensors
      2. 5.2 Object Appearance and Shading
      3. 5.3 Signals and Sampling
      4. 5.4 Image Features and Their Combination
      5. 5.5 Obtaining Depth
      6. 5.6 Active Vision
      7. 5.7 Other Sensors
      8. 5.8 Biological Vision
      9. 5.9 Further Reading
      10. 5.10 Problems
  12. Part Two: Representation and Planning
    1. 6 Representing and Reasoning About Space
      1. 6.1 Representing Space
      2. 6.2 Representing the Robot
      3. 6.3 Path Planning for Mobile Robots
      4. 6.4 Planning for Multiple Robots
      5. 6.5 Biological Mapping
      6. 6.6 Further Reading
      7. 6.7 Problems
    2. 7 System Control
      1. 7.1 Horizontal Decomposition
      2. 7.2 Vertical Decomposition
      3. 7.3 Hybrid Control Architectures
      4. 7.4 Middleware
      5. 7.5 High-Level Control
      6. 7.6 Alternative Control Formalisms
      7. 7.7 The Human--Robot Interface
      8. 7.8 Mobile Robot Software Development as Experimentation
      9. 7.9 Standard Software Toolkits
      10. 7.10 Further Reading
      11. 7.11 Problems
    3. 8 Pose Maintenance and Localization
      1. 8.1 Simple Landmark Measurement
      2. 8.2 Servo Control
      3. 8.3 Recursive Filtering
      4. 8.4 Non-Geometric Methods: Perceptual Structure
      5. 8.5 Correlation-Based Localization
      6. 8.6 Global Localization
      7. 8.7 Biological Approaches to Localization
      8. 8.8 Further Reading
      9. 8.9 Problems
    4. 9 Mapping and Related Tasks
      1. 9.1 Sensorial Maps
      2. 9.2 Geometric Maps
      3. 9.3 Topological Maps
      4. 9.4 Exploration
      5. 9.5 Further Reading
      6. 9.6 Problems
    5. 10 Robot Collectives
      1. 10.1 Categorizing Collectives
      2. 10.2 Control Architectures
      3. 10.3 Collective Communication
      4. 10.4 Sensing
      5. 10.5 Planning for Action
      6. 10.6 Formation Control
      7. 10.7 Localization
      8. 10.8 Mapping
      9. 10.9 Further Reading
      10. 10.10 Problems
    6. 11 Robots in Practice
      1. 11.1 Delivery Robots
      2. 11.2 Intelligent Vehicles
      3. 11.3 Robots for Survey and Inspection
      4. 11.4 Mining Automation
      5. 11.5 Space Robotics
      6. 11.6 Autonomous Aircraft
      7. 11.7 Military Reconnaissance
      8. 11.8 Bomb/Mine Disposal
      9. 11.9 Underwater Inspection
      10. 11.10 Agriculture/Forestry
      11. 11.11 Aids for the Disabled
      12. 11.12 Entertainment
      13. 11.13 Domestic Robots
      14. 11.14 Further Reading
      15. 11.15 Problems
    7. 12 The Future of Mobile Robotics
      1. 12.1 Locomotion
      2. 12.2 Sensors
      3. 12.3 Control
      4. 12.4 System Integration
      5. 12.5 Standardization
      6. 12.6 Future Directions
  13. Appendix A: Probability and Statistics
    1. A.1 Probabililty
    2. A.2 Some Simple Statistics
    3. A.3 Further Reading
    4. A.4 Problems
  14. Appendix B: Linear Systems, Matrices, and Filtering
    1. B.1 Linear Algebra
    2. B.2 Matrix Algebra
    3. B.3 Signals and Systems
    4. B.4 Fourier Theory
    5. B.5 Sampling and the Nyquist Theorem
    6. B.6 Further Reading
    7. B.7 Problems
  15. Appendix C: Markov Models
    1. C.1 Discrete Markov Process
    2. C.2 Hidden Markov Models
    3. C.3 Markov Decision Process
    4. C.4 POMDP
    5. C.5 Further Reading
    6. C.6 Problems
  16. Bibliography
  17. Index