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Intelligent Robotic Systems: Theory, Design and Applications

  • Book
  • © 1992

Overview

Authors:
  1. Kimon P. Valavanis

    1. Intelligent Robotic Systems Laboratory, The Center for Advanced Computer Studies, The University of Southwestern Louisiana, Lafayette, USA

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  2. George N. Saridis

    1. NASA Center for Intelligent Robotic Systems for Space Exploration, Rensselaer Polytechnic Institute, Troy, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 182)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xix
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  2. Introduction

    • Kimon P. Valavanis, George N. Saridis
    Pages 1-11

  3. A Review on Hierarchical and Expert Systems

    • Kimon P. Valavanis, George N. Saridis
    Pages 13-38

  4. On the General Theory of Intelligent Machines

    • Kimon P. Valavanis, George N. Saridis
    Pages 39-57

  5. The Mathematical Model for Intelligent Robotic Systems

    • Kimon P. Valavanis, George N. Saridis
    Pages 59-123

  6. Architectural Models for Intelligent Robotic Systems

    • Kimon P. Valavanis, George N. Saridis
    Pages 125-154

  7. Examples and Case Studies

    • Kimon P. Valavanis, George N. Saridis
    Pages 155-209

  8. Conclusions and Recommendations

    • Kimon P. Valavanis, George N. Saridis
    Pages 211-218

  9. Back Matter

    Pages 219-252
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Keywords

About this book

Since the late 1960s, there has been a revolution in robots and industrial automation, from the design of robots with no computing or sensorycapabilities (first-generation), to the design of robots with limited computational power and feedback capabilities (second-generation), and the design of intelligent robots (third-generation), which possess diverse sensing and decision making capabilities. The development of the theory of intelligent machines has been developed in parallel to the advances in robot design. This theory is the natural outcome of research and development in classical control (1950s), adaptive and learning control (1960s), self-organizing control (1970s) and intelligent control systems (1980s).
The theory of intelligent machines involves utilization and integration of concepts and ideas from the diverse disciplines of science, engineering and mathematics, and fields like artificial intelligence, system theory and operations research. The main focus and motivation is to bridge the gap between diverse disciplines involved and bring under a common cover several generic methodologies pertaining to what has been defined as machine intelligence. Intelligent robotic systems are a specific application of intelligent machines. They are complex computer controlled robotic systems equipped with a diverse set of visual and non visual sensors and possess decision making and problem solving capabilities within their domain of operation. Their modeling and control is accomplished via analytical and heuristic methodologies and techniques pertaining to generalized system theory and artificial intelligence.
Intelligent Robotic Systems: Theory, Design and Applications, presents and justifies the fundamental concepts and ideas associated with the modeling and analysis of intelligent robotic systems.
Appropriate for researchers and engineers in the general area of robotics and automation, Intelligent Robotic Systems is both a solid reference as well as a text for a graduate level course in intelligent robotics/machines.

Authors and Affiliations

  • Intelligent Robotic Systems Laboratory, The Center for Advanced Computer Studies, The University of Southwestern Louisiana, Lafayette, USA

    Kimon P. Valavanis

  • NASA Center for Intelligent Robotic Systems for Space Exploration, Rensselaer Polytechnic Institute, Troy, USA

    George N. Saridis

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