Intelligent Robotic Systems: Design, Planning, and Control (IFSR International Series in Systems Science and Systems Engineering (14))

Here is a comprehensive presentation of methodology for the design and synthesis of an intelligent complex robotic system, connecting formal tools from discrete system theory, artificial intelligence, neural network, and fuzzy logic. The necessary methods for solving real time action planning, coordination and control problems are described. A notable chapter presents a new approach to intelligent robotic agent control acting in a realworld environment based on a lifelong learning approach combining cognitive and reactive capabilities. Another key feature is the homogeneous description of all solutions and methods based on system theory formalism.

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Jacak (Johannes Kepler University, Linz, Austria) deals with the basic research issues associated with each subsystem of an intelligent robotic cell, and discusses how tools and methods from different discrete system theory, artificial intelligence, fuzzy set theory, and neural network analysis can address these issues. The first part gives detailed formal descriptions and solutions of problems in technological process planning and robot motion planning. The methods are for use in the off-line phase of design and synthesis. Part two treats real-time events based on multilevel coordination and control of robotic cells using neural network computing. Different on-line planning and control methods are described depending on the knowledge about the surrounding environment of the robotic agent. Annotation c. Book News, Inc., Portland, OR (booknews.com)