Paper Info
Title
Rapidly adapting artificial neural networks for autonomous navigation
Abstract
The ALVINN (Autonomous Land Vehicle In a Neural Network) project addresses the problem of training artificial neural networks in real time to perform difficult perception tasks. ALVINN ,is a back-propagation network that uses inputs from a video camera and an imaging laser rangefinder to drive the CMU Navlab, a modified Chevy van. This paper describes training techniques which allow ALVINN to learn in under 5 minutes to autonomously control the Navlab by watching a human driver's response to new situations. Using these techniques, ALVINN has been trained to drive in a variety of circumstances including single-lane paved and unpaved roads, multilane lined and unlined roads, and obstacle-ridden on- and off-road environments, at speeds of up to 20 miles per hour.
Year
Venue
Keywords
1990
NIPS
artificial neural network
Field
DocType
ISBN
Computer science,Real-time computing,Artificial intelligence,Laser rangefinder,Video camera,Artificial neural network,Machine learning
Conference
1-55860-184-8
Citations 
PageRank 
References 
8
1.16
4
Authors
1
Name
Order
Citations
PageRank
Dean Pomerleau11039283.23