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4 May 2009 GeoTrack: bio-inspired global video tracking by networks of unmanned aircraft systems
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Research from the Institute for Collaborative Biotechnologies (ICB) at the University of California at Santa Barbara (UCSB) has identified swarming algorithms used by flocks of birds and schools of fish that enable these animals to move in tight formation and cooperatively track prey with minimal estimation errors, while relying solely on local communication between the animals. This paper describes ongoing work by UCSB, the University of Florida (UF), and the Toyon Research Corporation on the utilization of these algorithms to dramatically improve the capabilities of small unmanned aircraft systems (UAS) to cooperatively locate and track ground targets. Our goal is to construct an electronic system, called GeoTrack, through which a network of hand-launched UAS use dedicated on-board processors to perform multi-sensor data fusion. The nominal sensors employed by the system will EO/IR video cameras on the UAS. When GMTI or other wide-area sensors are available, as in a layered sensing architecture, data from the standoff sensors will also be fused into the GeoTrack system. The output of the system will be position and orientation information on stationary or mobile targets in a global geo-stationary coordinate system. The design of the GeoTrack system requires significant advances beyond the current state-of-the-art in distributed control for a swarm of UAS to accomplish autonomous coordinated tracking; target geo-location using distributed sensor fusion by a network of UAS, communicating over an unreliable channel; and unsupervised real-time image-plane video tracking in low-powered computing platforms.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Prabir Barooah, Gaemus E. Collins, and João P. Hespanha "GeoTrack: bio-inspired global video tracking by networks of unmanned aircraft systems", Proc. SPIE 7321, Bio-Inspired/Biomimetic Sensor Technologies and Applications, 73210F (4 May 2009);

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