Accession Number : ADA311299
Title : Initial Results in Vision Based Road and Intersection Detection and Traversal.
Descriptive Note : Technical rept.,
Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
Personal Author(s) : Jochem, Todd M.
PDF Url : ADA311299
Report Date : APR 1995
Pagination or Media Count : 32
Abstract : The use of artificial neural networks in the domain of autonomous driving has produced promising results. ALVINN has shown that a neural system can drive a vehicle reliably and safely on many different types of roads, ranging from paved paths to interstate highways (9). The next step in the evolution of autonomous driving systems is to intelligently handle road junctions. In this paper, we present an addition to the basic ALVINN driving system which makes autonomous detection of roads and traversal of simple intersections possible. The addition is based on geometrically modelling the world, accurately imaging interesting parts of the scene using this model, and monitoring ALVINN's respouse to the created image.
Descriptors : *NEURAL NETS, *AUTONOMOUS NAVIGATION, IMAGE PROCESSING, POSITION(LOCATION), STEERING, ROBOTS, ACCURACY, INPUT OUTPUT PROCESSING, GROUND VEHICLES, ARTIFICIAL INTELLIGENCE, SYSTEMS ANALYSIS, ROADS, COMPUTER VISION, PIXELS, SURFACE NAVIGATION.
Subject Categories : Cybernetics
Land and Riverine Navigation and Guidance
Distribution Statement : APPROVED FOR PUBLIC RELEASE