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Computational Principles of Mobile Robotics
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Table of Contents

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. Representing and reasoning about space; 7. System control; 8. Pose maintenance and localization; 9. Mapping and related tasks; 10. Robot collectives; 11. Robots in practice; 12. The future of mobile robotics; Appendix A. Probability and statistics; Appendix B. Linear systems, matrices and filtering; Appendix C. Markov models.

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An advanced undergraduate/graduate text, emphasizing computation and algorithms for locomotion, sensing, and reasoning in mobile robots.

About the Author

Gregory Dudek is Professor of Computer Science and Director of the School of Computer Science at McGill University. He holds a James McGill Chair and is a member of the Center for Intelligent Machines, and has been co-author of over 150 refereed publications on robotics and computer vision. Michael Jenkin is a Professor of Computer Science and Engineering at York University. He has co-edited a series of eight books on human and machine vision.

Reviews

'... a good synthesis of robotics for computer science people, and is a useful tool for approaching the area.' Computing Reviews
'... clearly presents the range of topics covered in this multidisciplinary field.' Industrial Robot
'This book is an indispensable tool for any - both pre-university and university - course on mobile robotics. It covers the main topics related to any mobile robotic system, including hardware (locomotion and communication), sensors, navigation, path planning, mapping, and localization.' Ramon Gonzalez Sanchez, University of Almeria
"This book is an indispensable tool for any--both pre-university and university--course on mobile robotics. In relation to the first edition, this current one has been sufficiently updated. I recommend this book to researchers--particularly those who study localization or mapping--and doctoral students who are interested in investigating the latest approaches and techniques in the mobile robotics field." RAMON GONZALEZ SANCHEZ, Computing Reviews
"This work (1st. ed., CH, Nov'00, 38-1584) became an immediate resource for this reviewer for both research and teaching purposes. In the multidisciplinary area of robotics, it is not uncommon to find textbooks that describe the algorithms involved in robotic control, perception, planning, etc., but fail to provide the reader with the critical details necessary for implementation. For the majority of topics, Dudek (McGill Univ., Canada) and Jenkin (York Univ., Canada) present the necessary math to perform the computation and in some cases also provide pseudocode. References are included throughout. The text really shines in its handling of algorithms for perception, sensor fusion, and path planning. The appendixes review probability, statistics, linear systems, filters, and Markov models, but not with enough depth to provide an introduction to someone new to any one of these topics. This work is a bit too advanced for an introductory course on robotics, but it would be a great resource for an intermediate or advanced course on mobile robotics." R.S. STANSBURY, Embry-Riddle Aeronautical University
"...a great resource for an intermediate or advanced course on mobile robotics." CHOICE

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