Year
2023
File Attachment
finalpaper_407_0502023534.pdf772.48 KB
Abstract
Area survey and search/confirmation of nuclear/radioactive sources in public areas are challenging
and time-consuming tasks. When performed manually, the task also has an associated risk of
exposing the operators to unknown radiation. With the help of quadruped robots like the Boston
Dynamics Spot, these repeated tasks could be automated efficiently, alleviating the radiation risks to
inspectors. The Spot robot comes with its software development kit (SDK) for users to write
custom code in Python to control the robot. In this study, a cadmium zinc telluride (CdZnTe)
detector, namely M400 from H3D Inc. has been integrated with the Spot via a Spot-CORE payload
computer, allowing the robot to capture gamma spectra of background radiation and
nuclear/radioactive sources present in a facility. A machine-learning model was developed to use
radiation maps from the detector to predict the direction of the radiation source. Two missions have
been developed, area mapping and search. In the area mapping mission, the Spot robot walks in
fixed steps along a pre-recorded path and performs gamma measurements with the M400 detector.
In the search mission, a custom-built algorithm navigates the Spot robot to diverge from the path
toward the source location; and once in a preset distance to the source, the Spot robot will collect a
gamma spectrum for a long acquisition time, e.g., 5 minutes. In both missions, operators can also
use the graphic user interface to direct the robot to a specific location to collect confirmation spectra.
The paper will present the details of each mission along with the test results with a 133Ba radiation
source in a simulated facility.