Gaussian Process Regression of UGV Collected Gamma Radiation Data
Posted on 2021-05-07 - 11:29 authored by Andrew West
Gamma radiation data, SLAM (Simultaneous Localisation And Mapping) maps, MCNP 6 simulation results, and python code for interpolation using Gaussian Process Regression of radiation data collected by an Unmanned Ground Vehicle.
Locations include the Lancaster University Neutron Laboratory (LUNL) and the Jožef Stefan Institute (JSI) TRIGA Mark II research nuclear reactor.
Data was collected by the TORONE project, using a Clearpath Jackal UGV, equipped with CeBr3 scintillator detector and mixed field analyser. Point observations (location based on robot position estimates from SLAM) of gamma count rate is interpolated into a 2D estimated dosimetry map based on locations available for the robot to visit (denoted as free-space in the SLAM map).
CITE THIS COLLECTION
West, Andrew (2021). Gaussian Process Regression of UGV Collected Gamma Radiation Data. University of Manchester. Collection. https://doi.org/10.48420/c.5323571.v1
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FUNDING
TORONE - TOtal characterisation for Remote Observation in Nuclear Environments
Engineering and Physical Sciences Research Council
Robotics and Artificial Intelligence for Nuclear (RAIN)
Engineering and Physical Sciences Research Council
A centre for Advanced Digital Radiometric Instrumentation for Applied Nuclear Activities (ADRIANA)
Engineering and Physical Sciences Research Council
