Robot Learning by Visual Observation

This book presents programming by demonstration for robot learning from observations with a focus on the trajectory level of task abstraction
 

• Discusses methods for optimization of task reproduction, such as reformulation of task planning as a constrained optimization problem
• Focuses on regression approaches, such as Gaussian mixture regression, spline regression, and locally weighted regression
• Concentrates on the use of vision sensors for capturing motions and actions during task demonstration by a human task expert

In times of a growing worldwide demand for automation and robotics applications, as well as an aging population and a shrinking work force, the development of robots with capacity to learn by observation and abilities for visual perception of the environment with vision sensors emerges as an important means to mitigate the above problems. This book is a valuable reference for university professors, graduate students, robotics enthusiasts, and companies that seek to develop robots with such abilities.