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Proceedings Paper

AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles
Author(s): X. Sean Wang; Byung Suk Lee; Firooz Sadjadi
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Paper Abstract

Advances in sensor technology and image processing have made it possible to equip unmanned aerial vehicles (UAVs) with economical, high-resolution, energy-efficient sensors. Despite the improvements, current UAVs lack autonomous and collaborative operation capabilities, due to limited bandwidth and limited on-board image processing abilities. The situation, however, is changing. In the next generation of UAVs, much image processing can be carried out onboard and communication bandwidth problem will improve. More importantly, with more processing power, collaborative operations among a team of autonomous UAVs can provide more intelligent event detection capabilities. In this paper, we present ideas for developing a system enabling target recognitions by collaborative operations of autonomous UAVs. UAVs are configured in three stages: manufacturing, mission planning, and deployment. Different sets of information are needed at different stages, and the resulting outcome is an optimized event detection code deployed onto a UAV. The envisioned system architecture and the contemplated methodology, together with problems to be addressed, are presented.

Paper Details

Date Published: 5 May 2006
PDF: 7 pages
Proc. SPIE 6234, Automatic Target Recognition XVI, 62340Q (5 May 2006); doi: 10.1117/12.667844
Show Author Affiliations
X. Sean Wang, Univ. of Vermont (United States)
Byung Suk Lee, Univ. of Vermont (United States)
Firooz Sadjadi, Lockheed Martin (United States)

Published in SPIE Proceedings Vol. 6234:
Automatic Target Recognition XVI
Firooz A. Sadjadi, Editor(s)

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