Neural Networks in Robotics
Language: English
Published by Springer US, 1992
- Hardcover
- Used
Condition: Used - Very good
£ 110.52
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Zustand: Gut | Seiten: 580 | Sprache: Englisch | Produktart: Bücher | Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems. …
Seller Inventory # 1623657/203
- Title
- Neural Networks in Robotics
- Author
- Unbekannt
- Publisher
- Springer US
- Publication year
- 1992
- Condition
- Gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 079239268X
- ISBN 13
- 9780792392682
- Seller catalogs
- Bücher
On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented.
For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
"Synopsis" may belong to another edition of this title.
Review
University Computing, Vol.15/4, 1993
"About the title" may belong to another edition of this title.
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