Autonomous Mobile Robots
Planning, Navigation and Simulation
Published on 7. September 2023
Book
Paperback/Softback
1088 pages
978-0-443-18908-1 (ISBN)
Description
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.
Finally, the book presents fusion mechanisms to design hybrid algorithms.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Product notice
Paperback (trade)
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 54 mm
Weight
1426 gr
ISBN-13
978-0-443-18908-1 (9780443189081)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
09/2023
Academic Press
€195.00
Available for download
Person
Rahul Kala is an assistant professor at the Centre of Intelligent Robotics, Indian Institute of Information Technology, Allahabad, India, where he received his B.Tech. and M.Tech. degrees in information technology. He received his Ph.D. degree in cybernetics from the University of Reading, UK in 2013. Dr. Kala has authored four books, 100 scientific papers, and is an active reviewer of leading journals of the domain. He has received numerous scholarships and grants from the Government of India, and is a recipient of the Best PhD Dissertation award from the IEEE Intelligent Transportation Systems Society.
Content
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
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