Autonomous Mobile Robots: Planning, Navigation, and Simulation presents detailed coverage of the domain of robotics in motion planning and associated topics in navigation. This book covers numerous base planning methods from diverse schools of learning, including deliberative planning methods, reactive planning methods, task planning methods, fusion of different methods, and cognitive architectures. It is a good resource for doing initial project work in robotics, providing an overview, methods and simulation software in one resource. For more advanced readers, it presents a variety of planning algorithms to choose from, presenting the tradeoffs between the algorithms to ascertain a good choice.
Finally, the book presents fusion mechanisms to design hybrid algorithms.
1. Chapter 1. An introduction to robotics - p. 2 2. Chapter 2. Localization and mapping - p. 57 3. Chapter 3. Visual SLAM, planning, and control - p. 104 4. Chapter 4. Intelligent graph search basics - p. 152 5. Chapter 5. Graph search-based motion planning - p. 210 6. Chapter 6. Configuration space and collision checking - p. 262 7. Chapter 7. Roadmap and cell decomposition-based motion planning - p. 323 8. Chapter 8. Probabilistic roadmap - p. 358 9. Chapter 9. Rapidly-exploring random trees - p. 410 10. Chapter 10. Artificial potential field - p. 468 11. Chapter 11. Geometric and fuzzy logic-based motion planning - p. 539 12. Chapter 12. An introduction to machine learning and deep learning - p. 595 13. Chapter 13. Learning from demonstrations for robotics - p. 627 14. Chapter 14. Motion planning using reinforcement learning - p. 670 15. Chapter 15. An introduction to evolutionary computation - p. 715 16. Chapter 16. Evolutionary robot motion planning - p. 762 17. Chapter 17. Hybrid planning techniques - p. 809 18. Chapter 18. Multi-robot motion planning - p. 855 19. Chapter 19. Task planning approaches - p. 909 20. Chapter 20. Swarm and evolutionary robotics - p. 964 21. Chapter 21. Simulation systems and case studies - p. 999 22. Index - p. 1049
Autonomous Mobile Robots: Planning, Navigation, and Simulation presents detailed coverage of the domain of robotics in motion planning and associated topics in navigation. This book covers numerous base planning methods from diverse schools of learning, including deliberative planning methods, reactive planning methods, task planning methods, fusion of different methods, and cognitive architectures. It is a good resource for doing initial project work in robotics, providing an overview, methods and simulation software in one resource. For more advanced readers, it presents a variety of planning algorithms to choose from, presenting the tradeoffs between the algorithms to ascertain a good choice.
Finally, the book presents fusion mechanisms to design hybrid algorithms.
1. Chapter 1. An introduction to robotics - p. 2 2. Chapter 2. Localization and mapping - p. 57 3. Chapter 3. Visual SLAM, planning, and control - p. 104 4. Chapter 4. Intelligent graph search basics - p. 152 5. Chapter 5. Graph search-based motion planning - p. 210 6. Chapter 6. Configuration space and collision checking - p. 262 7. Chapter 7. Roadmap and cell decomposition-based motion planning - p. 323 8. Chapter 8. Probabilistic roadmap - p. 358 9. Chapter 9. Rapidly-exploring random trees - p. 410 10. Chapter 10. Artificial potential field - p. 468 11. Chapter 11. Geometric and fuzzy logic-based motion planning - p. 539 12. Chapter 12. An introduction to machine learning and deep learning - p. 595 13. Chapter 13. Learning from demonstrations for robotics - p. 627 14. Chapter 14. Motion planning using reinforcement learning - p. 670 15. Chapter 15. An introduction to evolutionary computation - p. 715 16. Chapter 16. Evolutionary robot motion planning - p. 762 17. Chapter 17. Hybrid planning techniques - p. 809 18. Chapter 18. Multi-robot motion planning - p. 855 19. Chapter 19. Task planning approaches - p. 909 20. Chapter 20. Swarm and evolutionary robotics - p. 964 21. Chapter 21. Simulation systems and case studies - p. 999 22. Index - p. 1049
