Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systemscovers the main topics from the wide area of mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB® script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization.
It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained.
1. Chapter 1: Introduction to Mobile Robotics - p. ix 2. Chapter 2: Motion Modeling for Mobile Robots - p. 11 3. Abstract - p. 13 4. 2.1 Introduction - p. 13 5. 2.2 Kinematics of Wheeled Mobile Robots - p. 13 6. 2.3 Motion Constraints - p. 32 7. 2.4 Dynamic Model of a Mobile System With Constraints - p. 48 8. Chapter 3: Control of Wheeled Mobile Systems - p. 59 9. Abstract - p. 61 10. 3.1 Introduction - p. 61 11. 3.2 Control to Reference Pose - p. 62 12. 3.3 Trajectory Tracking Control - p. 88 13. 3.4 Optimal Velocity Profile Estimation for a Known Path - p. 148 14. Chapter 4: Path Planning - p. 159 15. Chapter 5: Sensors Used in Mobile Systems - p. 206 16. Abstract - p. 207 17. 5.1 Introduction - p. 207 18. 5.2 Coordinate Frame Transformations - p. 208 19. 5.3 Pose Measurement Methods - p. 231 20. 5.4 Sensors - p. 283 21. Chapter 6: Nondeterministic Events in Mobile Systems - p. 288 22. Abstract - p. 289 23. 6.1 Introduction - p. 289 24. 6.2 Basics of Probability - p. 290 25. 6.3 State Estimation - p. 299 26. 6.4 Bayesian Filter - p. 304 27. 6.5 Kalman Filter - p. 337 28. 6.6 Particle Filter - p. 375 29. Chapter 7: Autonomous Guided Vehicles - p. 386 30. Chapter 8: Project Examples for Laboratory Practice - p. 418 31. Index - p. 483
Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systemscovers the main topics from the wide area of mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB® script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization.
It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained.
1. Chapter 1: Introduction to Mobile Robotics - p. ix 2. Chapter 2: Motion Modeling for Mobile Robots - p. 11 3. Abstract - p. 13 4. 2.1 Introduction - p. 13 5. 2.2 Kinematics of Wheeled Mobile Robots - p. 13 6. 2.3 Motion Constraints - p. 32 7. 2.4 Dynamic Model of a Mobile System With Constraints - p. 48 8. Chapter 3: Control of Wheeled Mobile Systems - p. 59 9. Abstract - p. 61 10. 3.1 Introduction - p. 61 11. 3.2 Control to Reference Pose - p. 62 12. 3.3 Trajectory Tracking Control - p. 88 13. 3.4 Optimal Velocity Profile Estimation for a Known Path - p. 148 14. Chapter 4: Path Planning - p. 159 15. Chapter 5: Sensors Used in Mobile Systems - p. 206 16. Abstract - p. 207 17. 5.1 Introduction - p. 207 18. 5.2 Coordinate Frame Transformations - p. 208 19. 5.3 Pose Measurement Methods - p. 231 20. 5.4 Sensors - p. 283 21. Chapter 6: Nondeterministic Events in Mobile Systems - p. 288 22. Abstract - p. 289 23. 6.1 Introduction - p. 289 24. 6.2 Basics of Probability - p. 290 25. 6.3 State Estimation - p. 299 26. 6.4 Bayesian Filter - p. 304 27. 6.5 Kalman Filter - p. 337 28. 6.6 Particle Filter - p. 375 29. Chapter 7: Autonomous Guided Vehicles - p. 386 30. Chapter 8: Project Examples for Laboratory Practice - p. 418 31. Index - p. 483
