Intelligent Robotic Systems: Theory, Design and ApplicationsSince 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. |
Contents
Chapter | 1 |
Section | 3 |
Chapter | 10 |
The Duality of the Concept of Entropy | 24 |
Knowledge Based Expert Systems | 32 |
ON THE GENERAL THEORY | 39 |
1 | 41 |
2 | 49 |
7 The Motion Gripper System Coordinators | 109 |
Discussion | 114 |
8 Generic Control System Configuration | 117 |
Definitions and the Principle of Increasing | 124 |
1 The Model for the Machine Reasoning | 129 |
3 The Model for the Machine Decision | 135 |
6 Hardware for the Probabilistic Method | 141 |
10 Hardware Coordinator Configuration | 147 |
Other editions - View all
Intelligent Robotic Systems: Theory, Design and Applications Kimon P. Valavanis,George N. Saridis No preview available - 1992 |
Intelligent Robotic Systems: Theory, Design and Applications Kimon P. Valavanis,George N. Saridis No preview available - 2012 |
Common terms and phrases
activities Ajm activities strings algorithm analytic approach Artificial Intelligence associated augmented activities bounded rationality chapter classified command table compiled command compiled input command complete and compatible Conditional entropies considered constraints coordination level corresponding cost function decision maker Decreasing Intelligence defined diagnostic differential entropy dispatcher entropy rate execution devices execution level expert system expert system cell flanges formulation forward chaining Gripper hardware hierarchically intelligent control Increasing Precision inference engine Information Theory intelligent control Intelligent Machines Intelligent Robotic Systems knowledge based systems line feedback information long term memory Machine Intelligence machine planning machine reasoning manipulator mathematical Motion System Coordinator object or tool operations optimal ordered activities organization level partition law performance permutation Petri nets pipes Precision with Decreasing principle of Increasing probabilistic probability distribution function procedures random variables repetitive events Saridis shown in Figure specific stored structure task plan task sequence uncertainty Vision System Coordinator workspace environment