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Proceedings Paper

Knowledge Based Vision For Terrestrial Robots
Author(s): Daryl T. Lawton; Tod S. Levitt; Patrice Gelband
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Paper Abstract

The Knowledge Based Vision Project1,2 is concerned with developing terrain recognition and modeling capabilities for an au land vehicle. For functioning in realistic outdoor environments, we are assuming a vehicle with a laser range finder, controllable cameras, and limited inertial sensing. The range finder is used for mapping and navigating through the immediate environment. The cameras are used for object recognition and recognizing distant landmarks beyond the access of the range sensor. We are assuming the vehicle has realistically limited perceptual and object recognition capabilities. In particular, it will see things that it won't be familiar with and can't recognize, but which can be described as stable visual perceptions. The vehicle will not always be able to recognize the same object as being identical from very different points of view. It will have limited, inexact, and undetailed a prior terrain information generally in the form of labeled grid data. One of the basic functions of the vehicle is to elaborate this terrain map of the environment. Another is to successfully navigate through the environment using landmarks.

Paper Details

Date Published: 5 January 1989
PDF: 6 pages
Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); doi: 10.1117/12.948954
Show Author Affiliations
Daryl T. Lawton, Advanced Decision Systems (United States)
Tod S. Levitt, Advanced Decision Systems (United States)
Patrice Gelband, Advanced Decision Systems (United States)

Published in SPIE Proceedings Vol. 1003:
Sensor Fusion: Spatial Reasoning and Scene Interpretation
Paul S. Schenker, Editor(s)

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