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Kai Vetter's Group Awarded DTRA Grant

Wednesday, Aug 23rd 2017

Professor Kai Vetter's group has been awarded a Defense Threat Reduction Agency (DTRA) grant.  The proposal, "New Concepts for Mobile Radiation Detection and Mapping Systems", will receive three years of funding.  

Abstract:

Recent advances in detector materials and readouts, machine vision, and autonomous systems and their control enable unprecedented capabilities in the search, localization, and characterization of nuclear and radiological materials. The integration of these advancements into autonomous platforms, such as small, unmanned aerial systems (sUAS), will significantly enhance the speed and accuracy in the detection and mapping of nuclear materials, particularly in complex and inaccessible environments while minimizing the exposure of the warfighter to hazards. We propose to study the fundamental properties of the relevant sensing and control components to enable a network of mobile sensors. The sensing components consist of new generations of organic scintillators and their associated solid-state photodetectors. Fundamental properties in the design, fabrication, and operation of these new materials will be explored to enable their full utilization and to enhance the sensitivity and specificity in the detection of gamma rays and neutrons associated with special nuclear materials. Techniques to 3D print these materials will be explored and their utilization as structural components of detection systems and platforms as well as their arrangement to modulate and moderate incident radiation to improve localization capabilities. These basic aspects will be studied in combination with machine vision concepts required for the control of the mobile detection units to enable the mapping and reconstruction of 3-D environments and the fusion with radiological data. The control components entail new concepts in the effective deployment of mobile networks to minimize the search time utilizing algorithms to compute theoretic quantities represented as probability distributions over the environment states. New concepts in the localization, mapping, and visualization will be explored along with the multi-dimensional set of data to optimize the realtime control of multiple sensing platforms employing information theoretical control concepts.