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Proceedings Paper

Multisensor fusion for decision-based control cues
Author(s): Linda Ann Gee; Mongi A. Abidi
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Paper Abstract

Data acquired form multiple sensors provides a means for defining a knowledge base and a current situation scenario. The data is accepted and integrated as intelligence with the use of signal- and symbol-level fusion to translate the raw data into intelligence information that can be used to baseline the knowledge of a control system. An application of this technique is applied to a robotic inspection and dismantlement system. This system is used to dismantle material sin a potentially hazardous environment that involves nuclear waste. The objective is to gather information about the environment using a suite of sensors to include range, electro-optical and proximity sensors to develop a current situation and initiate cues to the control system. By including evidential reasoning in the fusion process, all of the data that is gathered can be used to build the knowledge base where lower belief factors are attributed to things with significant uncertainty. Logical inferences are also incorporated to develop certainty measures and truth values. The results suggest an approach to multisensor fusion for decision-based control using a knowledge base and current situation scenario framework.

Paper Details

Date Published: 4 August 2000
PDF: 9 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395075
Show Author Affiliations
Linda Ann Gee, Univ. of Tennessee/Knoxville (United States)
Mongi A. Abidi, Univ. of Tennessee/Knoxville (United States)


Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)

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