ALVINN: An Autonomous Land Vehicle in a Neural Network

Part of Advances in Neural Information Processing Systems 1 (NIPS 1988)

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Authors

Dean A. Pomerleau

Abstract

ALVINN (Autonomous Land Vehicle In a Neural Network) is a 3-layer back-propagation network designed for the task of road following. Cur(cid:173) rently 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 perfOIm the task differs dra(cid:173) matically when the networlc 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.