About the book
This book will be a collection of state-of-the-art chapters in methods and numerous applications of robot motion planning. Motion planning is a fundamental key-function for all navigational modalities of rolling, walking, flying and swimming robots, as well as trajectory generation and control of robotic arms. Motion, path and tasks planning are correlated tasks that are critical for industrial, manufacture and service robotic missions. Those tasks depend on their cyber-physical planning interactions of the robot's mechanisms, actuators motion, and end-effector tasks.
This book will collect different approaches to robot motion planning in artificial intelligence algorithms and dynamic modeling and control methods. The intelligent robotics approach includes traditional AI methods grouped in Graph search, Machine Learning and Reinforcement Learning algorithms. Moreover, the methods based on dynamic modeling and control include geometric and algebraic models, differential ordinary/partial equations, Kalman filters for state estimation and sensory-motor feedback approaches. Likewise, this book will provide the point of views developed for path generation and motion tracking in both, deterministic and probabilistic perspectives.