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PADUA RADIOLOGICAL SEARCH SYSTEM

Date Issued
December 15, 2019
Author(s)
Magocs, Benjamin
Advisor(s)
Howard Hall, John Auxier II
Additional Advisor(s)
Robert Bond
Matthew Cook
Zhili Zhang
John Schmisseur
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/26947
Abstract

The primary intention of this project was to improve upon the current state-of-the-art radiological detection methods by integrating autonomous control methods, Bayesian statistics, Savitzky-Golay filtering, other search methods, and novel swarming techniques together to create a single push-button multi-agent radiation search algorithm (the Padua algorithm). The primary agents the algorithm was designed for onboard usage with were multirotor-type unmanned aerial vehicles (UAV’s) and, in certain portions of search, fixed wing UAV’s. The development of Padua for this project was performed entirely in simulation using the Python Dronekit SITL API. The final algorithm performed exceptionally well with the ability to narrow down the predicted location of a large radioactive source to only a few meters or less from a space that was 1 sq. km. in less than an hour.

Subjects

radioactive material ...

unmanned aircraft

autonomous aircraft c...

python

bayesian

CBRM

Degree
Doctor of Philosophy
Major
Engineering Science
Embargo Date
December 15, 2020
File(s)
Thumbnail Image
Name

utk.ir.td_12891.pdf

Size

16.06 MB

Format

Adobe PDF

Checksum (MD5)

332e7565d7f1f29b620a9f0e9f22fe05


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