Neural Network Perception for Mobile Robot Guidance

Name: Neural Network Perception for Mobile Robot Guidance
Brand: Springer-Verlag New York Inc.
SKU: 9781461364009
Price: 115.87 EUR
Availability: InStock

Автор: Dean A. Pomerleau

Език:

Корици: С меки корици

Издател: Springer-Verlag New York Inc.

Наличност: Външен склад в ограничено количество

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115.87 € 226.62 лв

Vision-based mobile robot guidance has proved difficult for classical machine vision methods because...

Информация за книгата

Автор

Dean A. Pomerleau

Език

Английски език

Корици

Книга - С меки корици

Издадена

2012

страници

191

EAN

9781461364009

ISBN

1461364000

Enbook ID

02016374

Издател

Springer-Verlag New York Inc.

Теглоt

332

Размери

155 x 235 x 12

Пълно описание

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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Neural Network Perception for Mobile Robot Guidance

Информация за книгата

Пълно описание

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