Description
By: Aude Billard, Sina Mirrazavi, Nadia Figueroa | Series: Intelligent Robotics and Autonomous Agents series
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises.
This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills.
Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control .
Features for teaching in each chapter:
applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises.
This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills.
Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control .
Features for teaching in each chapter:
You may also like
熱銷中 Top Trending
Dog Man 14: Dog Man: Big Jim Believes: A Graphic Novel (Dog Man #14)
Sale priceHK$85.00
Regular priceHK$150.00
In stock
Dragon Masters #30 Vortex of the Chaos Dragon (Branches) (Tracey West)
Sale priceHK$55.00
Regular priceHK$69.00
In stock
Dragon Masters #29 (正版) Magic of the Wizard Dragon (Branches) (Tracey West)
Sale priceHK$48.00
Regular priceHK$69.00
In stock
Dragon Masters #28 (正版) Night of the Dream Dragon (Branches) (Tracey West)
Sale priceHK$48.00
Regular priceHK$69.00
In stock
Beast Quest Ice and Fire (15 Books) (Adam Blade)
Sale priceHK$346.00
Regular priceHK$1,257.90
In stock
Magic Tree House Fact Tracker Graphic Novel: Space
Sale priceFrom HK$70.00
Regular priceHK$110.00
In stock
National Geographic Little Kids First Big Book of the World
Sale priceFrom HK$96.00
Regular priceHK$150.00
In stock