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.


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    Title :

    AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles


    Contributors:

    Conference:

    Automatic Target Recognition XVI ; 2006 ; Orlando (Kissimmee),Florida,United States


    Published in:

    Proc. SPIE ; 6234 ; 62340Q


    Publication date :

    2006-05-05





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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