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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. This edition includes advances in robotics and intelligent machines over the ten years prior to publication, 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…mehr
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. This edition includes advances in robotics and intelligent machines over the ten years prior to publication, 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.
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Gregory Dudek is Distinguished James McGill Professor of Computer Science at McGill University. He is also a member of the Center for Intelligent Machines, and associate member of Mila, and has been co-author of over 300 refereed publications on robotics, machine learning and computer vision. He has also served as a Vice President with Samsung Electronics and founding Lab Head for the Samsung AI Center in Montreal, Canada. With Michael Jenkin, he has played many roles in the field including co-founding Independent Robotics Inc, and established the Canadian Robotics Research Network.
Inhaltsangabe
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.
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.
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.
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.
Rezensionen
'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
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