Neural network-based vision processing for autonomous robot guidance
Conference Paper, Proceedings of SPIE Conference on Aerospace Sensing, Vol. 1469, pp. 121 - 128, August, 1991
Abstract
The autonomous land vehicle in a neural network (ALVINN) project addresses the problem of training artificial neural networks in real time to perform difficult perception tasks. ALVINN is a modular connectionist system that uses inputs from a video camera and an imaging laser rangefinder to guide the CMU Navlab, a modified Chevy van. This paper describes a technique for rapidly training expert networks for new driving circumstances. A rule-based integration scheme that uses a symbolic planning system to combine multiple experts is also presented.
BibTeX
@conference{Pomerleau-1991-15818,author = {Dean Pomerleau},
title = {Neural network-based vision processing for autonomous robot guidance},
booktitle = {Proceedings of SPIE Conference on Aerospace Sensing},
year = {1991},
month = {August},
volume = {1469},
pages = {121 - 128},
}
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