Eecient T Raining of Artiicial Neural Networks for Autonomous Navigation
نویسنده
چکیده
The ALVINN (Autonomous Land Vehicle In a Neural Network) project addresses the problem of training arti cial neural networks in real time to perform di cult perception tasks. ALVINN is a back-propagation network designed to drive the CMU Navlab, a modi ed Chevy van. This paper describes the training techniques which allow ALVINN to learn in under 5 minutes to autonomously control the Navlab by watching a human driver's reactions. Using these techniques ALVINN has been trained to 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 20 miles per hour.
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