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Proceedings Paper

Application of Dempster-Shafer theory to a novel control scheme for sensor fusion
Author(s): Robin R. Murphy
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Paper Abstract

The combination of imperfect evidence contributed by different sensors is a basic problem for sensor fusion in autonomous mobile robots. Current implementations of sensor fusion systems are restricted to fusing only certain classes of evidence because of the lack of a general framework for the combination of evidence. The authors approach to this problem is to first develop a model of the sensor fusion without committing to a particular theory of evidence, then to formulate a combination of evidence framework based on the requirements of the model. Their previous work has proposed such a model. This paper discusses the evidential demands of the model and one possible implementation using Dempster-Shafer theory. Three drawbacks of DS theory (computational intractability, weak assumptions of statistical independence, and counterintuitive averaging of strongly biased evidence) are eliminated by applying DS theory within the constraints of the model. An example based on simulated sensor data illustrates this application of Dempster-Shafer theory.

Paper Details

Date Published: 1 October 1991
PDF: 14 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48366
Show Author Affiliations
Robin R. Murphy, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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