Modeling, Learning and Control of Complex Dynamical Systems Toward Human-Robot Collaboration

This book offers readers a systematic exposition of the theoretical knowledge and application technology of Human-Robot Collaboration, Human-Robot Intelligence, and Human-Robot Dynamical Systems, filling an important gap in the current artificial intelligence research community. The highlights of this book include the critical concept of the Human-Robot Dynamical System and the pioneering technology of Human-Robot Dynamics Learning. Specifically, the Human-Robot Dynamical System represents a significant new research direction in the field of Human-Robot Intelligence. It encompasses the complex dynamical systems involved in human-robot collaboration and interaction applications, such as robot dynamics control, human behavior understanding, and human-robot motion-cognition-coupled interaction.

Human-Robot Dynamics Learning technology is designed specifically for Human-Robot Dynamical Systems. It is an innovative machine learning approach that combines techniques from artificial neural networks, control system theory, and classical mechanics. This technology excels in achieving precise mathematical expression and accurate modeling of the dynamic behavior of human-robot systems.

It provides an advanced framework for studying the theoretical and technological challenges in Human-Robot Collaboration and interaction applications, and it could offer a new research direction for developing the next generation of artificial intelligence.