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Proceedings Paper

Autonomous road navigation for unmanned ground vehicles
Author(s): Scott A. Speigle; Pat McIngvale; Keith Olson; Allen Scales; Karin R. Larsen
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Paper Abstract

The Navigation and Control Group, Missile Guidance Directorate, Research Development & Engineering Center of the U.S. Army Missile Command is conducting a program to develop and demonstrate a robust, low cost machine vision system for autonomous vehicles. This machine vision system has the requirement of providing robust classification of roads and obstacles over varying terrain, lighting, and weather. The focus of the development is to operate using a passive sensor suite of a color video camera and a black hot FLIR video camera. Machine vision algorithms have been developed and tested in a simulation environment using test sequences from video segments of various road types. This paper presents a novel approach to road and obstacle classification based on color video input. The paper begins by defining the problem and is followed by a discussion of the major functions of the simulation including the mission supervisor, the image server, the image processing algorithms, and concludes with experimental results.

Paper Details

Date Published: 30 June 1995
PDF: 11 pages
Proc. SPIE 2463, Synthetic Vision for Vehicle Guidance and Control, (30 June 1995); doi: 10.1117/12.212745
Show Author Affiliations
Scott A. Speigle, U.S. Army Missile Command (United States)
Pat McIngvale, U.S. Army Missile Command (United States)
Keith Olson, Nichols Research Corp. (United States)
Allen Scales, Nichols Research Corp. (United States)
Karin R. Larsen, Nichols Research Corp. (United States)


Published in SPIE Proceedings Vol. 2463:
Synthetic Vision for Vehicle Guidance and Control
Jacques G. Verly, Editor(s)

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