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Cited by 454

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Decentralized Cooperative Aerial Surveillance Using Fixed-Wing Miniature UAVs

Beard, R.W., McLain, T.W., Nelson, D.B., Kingston, D., Johanson, D.·2006·Proceedings of the IEEE

Abstract

Numerous applications require aerial surveillance. Civilian applications include monitoring forest fires, oil fields, and pipelines and tracking wildlife. Applications to homeland security include border patrol and monitoring the perimeter of nuclear power plants. Military applications are numerous. The current approach to these applications is to use a single manned vehicle for surveillance. However, manned vehicles are typically large and expensive. In addition, hazardous environments and operator fatigue can potentially threaten the life of the pilot. Therefore, there is a critical need for automating aerial surveillance using unmanned air vehicles (UAVs). This paper gives an overview of a cooperative control strategy for aerial surveillance that has been successfully flight tested on small (48-in wingspan) UAVs. Our approach to cooperative control problems can be summarized in four steps: 1) the definition of a cooperation constraint and cooperation objective; 2) the definition of a coordination variable as the minimal amount of information needed to effect cooperation; 3) the design of a centralized cooperation strategy; and 4) the use of consensus schemes to transform the centralized strategy into a decentralized algorithm. The effectiveness of the solution will be shown using both high-fidelity simulation and actual flight tests

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Crossref · 10.1109/jproc.2006.876930

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Metadata

Authors
Beard, R. W., McLain, T. W., Nelson, D. B., Kingston, D., & Johanson, D.
Venue
Proceedings of the IEEE
Published
2006-07
Volume
94
Issue
7
Pages
1306-1324
ISSN
  • 0018-9219 (ISSN-L)
  • 1558-2256
OpenAlex
W2010904712
Cited by
454
References
35
FWCI
20.94
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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