"This text provides an exceptional introduction to the multidisciplinary field of mobile robotics using handson examples in ROS 2 enabling students to explore concepts either in a simulation or using their own robot hardware. The new edition includes coverage of HRI, robot ethics, and AI techniques for end-to-end robot control"--
"This text provides an exceptional introduction to the multidisciplinary field of mobile robotics using handson examples in ROS 2 enabling students to explore concepts either in a simulation or using their own robot hardware. The new edition includes coverage of HRI, robot ethics, and AI techniques for end-to-end robot control"--
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.
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.
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.
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.
Rezensionen
'... a good synthesis of robotics for computer science people, and is a useful tool for approaching the area.' Computing Reviews
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