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Proceedings Paper

An extensible architecture for collaborative networked unmanned air vehicles operations
Author(s): Y.-L. Chen; M. Peot; J. Lee; T. Altshuler
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Paper Abstract

UAVs are a key element of the U. S. Army's vision for Force Transformation, and are expected to be employed in large numbers per FCS Unit of Action (UoA). This necessitates a multi-UAV level of autonomous collaboration behavior capability that meets RSTA and other mission needs of FCS UoAs. Autonomous Collaborative Mission Systems (ACMS) is an extensible architecture and behavior planning / collaborative approach to achieve this level of capability. The architecture is modular and the modules may be run in different locations/platforms to accommodate the constraints of available hardware, processing resources and mission needs. The modules and uniform interfaces provide a consistent and platform-independent baseline mission collaboration mechanism and signaling protocol across different platforms. Further, the modular design allows flexible and convenient extension to new autonomous collaborative behaviors to the ACMS through: adding new behavioral templates in the Mission Planner component; adding new components in appropriate ACMS modules to provide new mission specific functionality; adding or modifying constraints or parameters to the existing components, or any combination of these. We describe the ACMS architecture, its main features on extensibility, and updates on current spiral development status and future plans for simulations in this report.

Paper Details

Date Published: 26 October 2005
PDF: 9 pages
Proc. SPIE 5986, Unmanned/Unattended Sensors and Sensor Networks II, 59860K (26 October 2005); doi: 10.1117/12.634772
Show Author Affiliations
Y.-L. Chen, Rockwell Scientific Co., LLC (United States)
M. Peot, Rockwell Scientific Co., LLC (United States)
J. Lee, Rockwell Scientific Co., LLC (United States)
T. Altshuler, Rockwell Scientific Co., LLC (United States)


Published in SPIE Proceedings Vol. 5986:
Unmanned/Unattended Sensors and Sensor Networks II
Edward M. Carapezza, Editor(s)

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