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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
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Neural Networks in Robotics (Paperback, Softcover reprint of the original 1st ed. 1993)
Loot Price: R4,808
Discovery Miles 48 080
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Neural Networks in Robotics (Paperback, Softcover reprint of the original 1st ed. 1993)
Series: The Springer International Series in Engineering and Computer Science, 202
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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.
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