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- Dean A. Pomerleau Computer Science Department, Carnegie Mellon University, Pittsburgh, PA
Computer Science Department, Carnegie Mellon University, Pittsburgh, PA
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NIPS'88: Proceedings of the 1st International Conference on Neural Information Processing SystemsJanuary 1988Pages 305–313
Published:01 January 1988Publication History
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NIPS'88: Proceedings of the 1st International Conference on Neural Information Processing Systems
ALVINN: an autonomous land vehicle in a neural network
Pages 305–313
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ABSTRACT
ALVINN (Autonomous Land Vehicle In a Neural Network) is a 3-layer back-propagation network designed for the task of road following. Currently ALVINN takes images from a camera and a laser range finder as input and produces as output the direction the vehicle should travel in order to follow the road. Training has been conducted using simulated road images. Successful tests on the Carnegie Mellon autonomous navigation test vehicle indicate that the network can effectively follow real roads under certain field conditions. The representation developed to perform the task differs dramatically when the network is trained under various conditions, suggesting the possibility of a novel adaptive autonomous navigation system capable of tailoring its processing to the conditions at hand.
References
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ALVINN: an autonomous land vehicle in a neural network
Computing methodologies
Artificial intelligence
Computer vision
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Machine learning
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NIPS'88: Proceedings of the 1st International Conference on Neural Information Processing Systems
January 1988
807 pages
- Editor:
- D. S. Touretzky
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MIT Press
Cambridge, MA, United States
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- Published: 1 January 1988
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