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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
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Neural Network Perception for Mobile Robot Guidance (Hardcover, 1993 ed.)
Loot Price: R2,761
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Neural Network Perception for Mobile Robot Guidance (Hardcover, 1993 ed.)
Series: The Springer International Series in Engineering and Computer Science, 239
Expected to ship within 18 - 22 working days
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Vision-based mobile robot guidance has proved difficult for
classical machine vision methods because of the diversity and
real-time constraints inherent in the task. This book describes a
connectionist system called ALVINN (Autonomous Land Vehicle In a
Neural Network) that overcomes these difficulties. ALVINN learns to
guide mobile robots using the back-propagation training algorithm.
Because of its ability to learn from example, ALVINN can adapt to
new situations and therefore cope with the diversity of the
autonomous navigation task. But real world problems like
vision-based mobile robot guidance present a different set of
challenges for the connectionist paradigm. Among them are: how to
develop a general representation from a limited amount of real
training data; how to understand the internal representations
developed by artificial neural networks; how to estimate the
reliability of individual networks; how to combine multiple
networks trained for different situations into a single system; how
to combine connectionist perception with symbolic reasoning. Neural
Network Perception for Mobile Robot Guidance presents novel
solutions to each of these problems. Using these techniques, the
ALVINN system can learn to control an autonomous van in under 5
minutes by watching a person drive. Once trained, individual ALVINN
networks can drive in a variety of circumstances, including
single-lane paved and unpaved roads, and multi-lane lined and
unlined roads, at speeds of up to 55 miles per hour. The techniques
also are shown to generalize to the task of controlling the precise
foot placement of a walking robot.
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