Neural Networks in Robotics (The Springer International Series in Engineering and Computer Science, 202). This item is unavailable.
Language: English
Published by Springer, 1992
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Ancien livre de bibliothèque avec équipements. Edition 1992. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1992. Ammareal gives back up to 15% of this item's net price to charity organizations.
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- Title
- Neural Networks in Robotics (The Springer International Series in Engineering and Computer Science, 202)
- Publisher
- Springer
- Publication year
- 1992
- Condition
- Très bon
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 079239268X
- ISBN 13
- 9780792392682
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.
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.
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Review
` Given the potential of neural networks to reduce the design complexity of control systems through learning, this book is essential for those involved in the research and development of robotic control systems. '
University Computing, Vol.15/4, 1993
University Computing, Vol.15/4, 1993
"About the title" may belong to another edition of this title.
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