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Proceedings Paper

Unmanned guided vehicle system
Author(s): John F. Gilmore; Harold Forbes; Kevin Payne; Khalid J. Elibiary
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Paper Abstract

Unmanned guided vehicles (UGV) require the ability to visually understand the objects contained within their operating environments in order to locally guide vehicles along a globally determined route. Several large scale programs have been funded over the past decade that have created multimillion dollar prototype vehicles incapable of functioning outside of their initial test track environment. This paper describes the Unmanned Guided Vehicle System (UGVS) developed for the US Army Missile Command for operation in natural terrain. The goal of UGVS is to develop a real-time system adaptive to a range of terrain environments (e.g. roads, open fields, wooded clearings, forest areas) and seasonal conditions (e.g., fall, winter, summer, spring). UGVS consists of two primary processing activities. First, the UGVS vision system is tasked with determining the location of gravel roads in video imagery, detecting obstacles in the vehicles path, identifying distant road spurs, and assigning a classification confidence to each image component. Second, the guidance and navigation system computes the global route the vehicle should pursue, utilizes image classification results to determine obstructions in the local vehicle path, computes navigation commands to drive the vehicle around hazardous obstacles, correlates visual road spur cues with global route digital maps, and provides the navigation commands to move the vehicle forward. Results of UGVS working in a variety terrain environments are presented to reinforce system concepts.

Paper Details

Date Published: 30 June 1995
PDF: 10 pages
Proc. SPIE 2463, Synthetic Vision for Vehicle Guidance and Control, (30 June 1995); doi: 10.1117/12.212746
Show Author Affiliations
John F. Gilmore, Georgia Institute of Technology (United States)
Harold Forbes, Georgia Institute of Technology (United States)
Kevin Payne, Georgia Institute of Technology (United States)
Khalid J. Elibiary, Georgia Institute of Technology (United States)

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

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