New edition of an advanced undergraduate/graduate text, emphasizing computation and algorithms for locomotion, sensing, and reasoning in mobile robots.
New edition of an advanced undergraduate/graduate text, emphasizing computation and algorithms for locomotion, sensing, and reasoning in mobile robots.
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.
Inhaltsangabe
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.
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.
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.
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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