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.

• 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 Learning20. Swarm and Evolutionary Robotics21. Simulation Systems and Case Studies

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.

• 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 Learning20. Swarm and Evolutionary Robotics21. Simulation Systems and Case Studies

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.

• 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 Learning20. Swarm and Evolutionary Robotics21. Simulation Systems and Case Studies