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. An Introduction to Robotics
2. Localization, Mapping, and Control
3. An Introduction to Motion Planning with Bug Algorithms
4. Intelligent Graph Search Basics
5. Graph Search based Motion Planning
6. Configuration Space and Collision Checking
7. Roadmap and Cell Decomposition based Motion Planning
8. Probabilistic Roadmap
9. Rapidly-exploring Random Trees
10. Artificial Potential Field
11. Geometric and Fuzzy-Logic based Motion Planning
12. An Introduction to Machine Learning and Neural Networks
13. Learning-based Robot Motion Planning
14. An Introduction to Evolutionary Computation
15. Evolutionary Robot Motion Planning
16. Hybrid Planning Techniques
17. Multi-Robot Motion Planning
18. Task Planning Approaches
19. Motion Planning in Uncertainties and Reinforcement Learning
20. Swarm and Evolutionary Robotics
21. Simulation Systems and Case Studies
