Application of Dempster-Shafer theory to a novel control scheme for sensor fusion

Robin R. Murphy

doi:10.1117/12.48366

1 October 1991 Application of Dempster-Shafer theory to a novel control scheme for sensor fusion

Robin R. Murphy

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48366
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

Robin R. Murphy "Application of Dempster-Shafer theory to a novel control scheme for sensor fusion", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48366

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