9781402016301 - Intelligent Control of Robotic Systems (Intelligent Systems, Control and Automation: Science and Engineering, 25, Band 25) von Katic, D.; Vukobratovic, M. (4 Ergebnisse)

Zustand: New. In.

Gebunden. Zustand: New. As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabili.

Zustand: New. Covers the theoretical and application aspects of neural networks, fuzzy logic, genetic algorithms and hybrid intelligent techniques in robotics. This work emphasises the development of efficient learning rules for robotic connectionist training and synthesis of neural learning algorithms for low-level control in the domain of compliance tasks. Series: Intelligent Systems, Control and Automation: Science and Engineering. Num Pages: 296 pages, biography. BIC Classification: TJFM1. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 19. Weight in Grams: 628. . 2003. Hardback. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems.