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Autor(en): 
  • Hong Cheng
  • Cong Wang
  • Jingting Zhang
  • Chengzhi Yuan
  • Modeling, Learning and Control of Complex Dynamical Systems: Toward Human-Robot Collaboration 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (Oktober 2026)  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / Complex Dynamical System / deterministic learning theory / Dynamic system theory / human-robot collaboration / Human-Robot Dynamical System / Human-Robot Dynamics Learning / Human-Robot Intelligence
    ISBN:  9789819218035 
    EAN-Code: 
    9789819218035 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  205 
    Illustration:  XIV, 191 p. 1 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    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.

      
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