A fuzzy-logic architecture for autonomous multisensor data fusion

Fuzzy logic techniques have become popular to address various processes for multisensor data fusion. Examples include the following: (1) fuzzy membership functions for data association; (2) evaluation of alternative hypotheses in multiple hypothesis trackers; (3) fuzzy-logic-based pattern recognitio...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 1996-06, Vol.43 (3), p.403-410
Main Authors: Stover, J.A., Hall, D.L., Gibson, R.E.
Format: Article
Language:English
Subjects:
Applied sciences
Automata. Logic controller
Automatic control
Computer science
control theory
systems
Control systems
Control theory. Systems
Exact sciences and technology
Fuzzy logic
Laboratories
Mobile robots
Object recognition
Pattern recognition
Process control
Remotely operated vehicles
Resource management
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Summary:Fuzzy logic techniques have become popular to address various processes for multisensor data fusion. Examples include the following: (1) fuzzy membership functions for data association; (2) evaluation of alternative hypotheses in multiple hypothesis trackers; (3) fuzzy-logic-based pattern recognition (e.g., for feature-based object identification); and (4) fuzzy inference schemes for sensor resource allocation. These approaches have been individually successful but are limited to only a single subprocess within a data fusion system. At The Pennsylvania State University, Applied Research Laboratory, a general-purpose fuzzy-logic architecture has been developed that provides for control of sensing resources, fusion of data for tracking, automatic object recognition, control of system resources and elements, and automated situation assessment. This general architecture has been applied to implement an autonomous vehicle capable of self-direction, obstacle avoidance, and mission completion. The fuzzy logic architecture provides interpretation and fusion of multisensor data (i.e., perception) as well as logic for process control (action). This paper provides an overview of the fuzzy-logic architecture and a discussion of its application to data fusion in the context of the Department of Defense (DoD) Joint Directors of Laboratories (JDL) Data Fusion Process Model. A new, robust, fuzzy calculus is introduced. An application example is provided.
ISSN:0278-0046
1557-9948
DOI:10.1109/41.499813