Autonomous Distributed 3D Radiation Field Estimation for Nuclear Environment Characterization
Frank Mascarich, Paolo De Petris, Huan Nguyen, Nikhil Khedekar, Kostas Alexis
Abstract
This paper contributes a method designed to enable autonomous distributed 3D nuclear radiation field mapping. The algorithm uses a single radiation sensor and a sequence of spatially distributed and robotically acquired radiation measurements across a discretized 3D grid to derive a radiation gradient. The derived gradient is probabilistically propagated to unknown components of the map to further guide a curiosity-driven path planner by identifying the next most radiologically informative point given available information. To demonstrate the method, we develop a resilient micro flying robot capable of autonomous GPS-denied navigation that integrates a Thallium–doped Cesium Iodide (CsI(Tl)) scintillator and Silicon Photomultiplier (SiPm) combined with custom–built pulse counting circuitry. A set of experimental studies is presented inside an indoor facility within which actual radioactive uranium ore sources have been distributed.
BibTeX
@inproceedings{icra2021_autonomousdistri,
title = {Autonomous Distributed 3D Radiation Field Estimation for Nuclear Environment Characterization},
author = {Frank Mascarich and Paolo De Petris and Huan Nguyen and Nikhil Khedekar and Kostas Alexis},
booktitle = {ICRA 2021},
year = {2021}
}