Human-Robot Interaction Control Using Reinforcement Learning by Wen Yu, Adolfo Perrusquía (IEEE Press Series on Systems Science and Engineering)
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Overview: A comprehensive exploration of the control schemes of human-robot interactions
In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation.
Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control.
The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics.
Genre: Non-Fiction > Educational
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