Abstract

The Army currently employs heterogeneous unattended ground sensors (UGSs) using a sparse deployment to maximize coverage, minimize pilferage and to monitor terrain bottlenecks. A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the US Army Research Laboratory (ARL) is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks as part of a US Army contract<sup>1</sup> with the Institute for Collaborative Biotechnologies (ICB). The ICB program is developing a new system consisting of novel bio-inspired software algorithms for autonomous operations that will leverage proven research to monitor sensor networks from extended ranges, that will collect data in a timely fashion, that will collaboratively control the motion of a sparse network of collectors (e.g., UAVs) using bio-inspired sampling, that will accurately detect and localize field events and will fuse and classify sensed data. A new bio-inspired event discovery technique will enable fusion of sensor observations at low SNR without requiring a prior model for the event signature; this is a first step towards sensor networks that are capable of learning. The program will also provide both laboratory and field demonstrations of these capabilities supported through ARL by leveraging available resources.

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