Computational Principles of Mobile Robotics

A graduate textbook providing a comprehensive introduction to mobile robotics, with hands-on examples in ROS 2.

Gregory Dudek (Author), Michael Jenkin (Author)

9781108498470, Cambridge University Press

Hardback, published 8 February 2024

450 pages
26 x 18.5 x 3 cm, 1.016 kg

'… a great resource for an intermediate or advanced course on mobile robotics.' R. S. Stansbury, Choice

Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary field of mobile robotics, which lies at the intersection of artificial intelligence, computational vision, and traditional robotics. Written for advanced undergraduates and graduate students in computer science and engineering, the book covers algorithms for a range of strategies for locomotion, sensing, and reasoning. The new edition includes recent advances in robotics and intelligent machines, including coverage of human-robot interaction, robot ethics, and the application of advanced AI techniques to end-to-end robot control and specific computational tasks. This book also provides support for a number of algorithms using ROS 2, and includes a review of critical mathematical material and an extensive list of sample problems. 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.

Acknowledgments
Preface
1. Overview and motivation
2. Fundamental problems
Part I. Locomotion and Perception: 3. Mobile robot hardware
4. Non-visual sensors and algorithms
5. Visual sensors and algorithms
Part II. Representation and Planning: 6. Deep learning for robots
7. Planning in, representing and reasoning about space
8. System control
9. Pose maintenance and localization
10. Mapping and related tasks
11. Robot collectives
12. Human-robot interaction
13. Robot ethics
14. Robots in practice
15. The future of mobile robotics
Appendix A. Fictional robots
Appendix B. Probability and statistics
Appendix C. Linear systems, matrices and filtering
Appendix D. Markov models
Bibliography
Index.

Subject Areas: Image processing [UYT]