A fuzzy-logic architecture for autonomous multisensor data fusion

Stover, J.A.; Hall, David L.; Gibson, Ronald E.

doi:10.1109/41.499813

Cited by 113 publications

(50 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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. ( Stover et al (1996)) There are many more fundamental contributions to the field by others, the above list can only be a small cross section due to limited space.…”

Section: Hagras Et Al (2003) Describes the Use Of Intelligent Autonomentioning

confidence: 99%

The Modular Intelligent Being: Review and a Proposal

Veres

2005

IFAC Proceedings Volumes

View full text Add to dashboard Cite

The paper provides a review and addresses the problem of creating a modular hardware system that can be effortlessly reconfigured by developers of autonomous intelligent control systems for mission type task execution in realtime physical environments. The idea is to allow for a common hardware platform which enables algorithmic results to be compared, accumulated and properly assessed by the research community. Such a single platform can then be used by researchers of autonomous systems in their research to speed up progress.

show abstract

Section: Hagras Et Al (2003) Describes the Use Of Intelligent Autonomentioning

confidence: 99%

The Modular Intelligent Being: Review and a Proposal

Veres

2005

IFAC Proceedings Volumes

View full text Add to dashboard Cite

show abstract

“…The IC needs to determine if the object detected is an "object of interest", i.e., an object worth investigating further. The processing structure used to determine this is the CINet [9][10][11] . CINets establish confidence factors (values between 0 and 1) for the set of inferred properties defined for a particular class.…”

Section: A Uav Ic Perception Modulementioning

confidence: 99%

“…A key capability of the Perception module is to make correct inferences and recognize the existence of properties in its internal models of external objects (Representational Classes) from incomplete and potentially erroneous input data. The Perception module contains data fusion algorithms and Continuous Inference Networks (CINets) [9][10][11] . The data fusion algorithms are responsible for fusing new sensor data so that the existing Representational Classes can be updated.…”

Section: A Perceptionmentioning

confidence: 99%

Intelligent Unmanned Air Vehicle Flight Systems

Miller

Minear

Niessner

et al. 2007

Journal of Aerospace Computing, Information, and Communication

View full text Add to dashboard Cite

This paper describes an intelligent autonomous airborne flight capability that is being used as a test bed for future technology development. The unmanned air vehicles (UAVs) fly under autonomous control of both an onboard computer and an autopilot. The onboard computer provides the mission control and runs the autonomous Intelligent Controller (IC) software while the autopilot controls the vehicle navigation and flight control. The autonomous airborne flight system is described in detail. An IC architecture directly applicable to the design of unmanned vehicles is also presented. The UAVs may operate independently or in cooperation with one another to carry out a specified mission. The intelligent UAV flight system is used to evaluate and study autonomous UAV control as well as multi-vehicle collaborative control.

show abstract

“…Fuzzy as the mean for the data-fusion have been mostly used as a tool to fuse the data retrieved from multisensor [5], [6] or more recently it is used in fusing position signals from Global Positioning Systems (GPS) and inertial navigation systems (INS) for autonomous mobile vehicles [7]. Moreover, the potential of applying fuzzy logic techniques in traffic and transportation systems analysis and control are also been discussed in few articles [8], [9].…”

Section: Introductionmentioning

confidence: 99%