NDLI: A fuzzy-logic architecture for autonomous multisensor data fusion

Content Provider	IEEE Xplore Digital Library
Author	Stover, J.A. Hall, D.L. Gibson, R.E.
Copyright Year	1982
Abstract	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.
Sponsorship	IEEE Industrial Electronics Society
Starting Page	403
Ending Page	410
Page Count	8
File Size	1016917
File Format	PDF
ISSN	02780046
Volume Number	43
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Automatic control Control systems Pattern recognition Resource management Laboratories Object recognition Remotely operated vehicles Mobile robots Process control
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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