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Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations
Effective radioactive hotspot localization and detection is limited by sensor characteristics (i.e., the long acquisition time and poor angular resolution AR of a gamma camera) that significantly degrade the performance of autonomous exploration in terms of the completion time and accuracy. The goal...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358856/ https://www.ncbi.nlm.nih.gov/pubmed/30642085 http://dx.doi.org/10.3390/s19020292 |
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author | Ardiny, Hadi Witwicki, Stefan Mondada, Francesco |
author_facet | Ardiny, Hadi Witwicki, Stefan Mondada, Francesco |
author_sort | Ardiny, Hadi |
collection | PubMed |
description | Effective radioactive hotspot localization and detection is limited by sensor characteristics (i.e., the long acquisition time and poor angular resolution AR of a gamma camera) that significantly degrade the performance of autonomous exploration in terms of the completion time and accuracy. The goal of this research is to study effective exploration algorithms that take into account these specific sensor limitations. These exploration algorithms are adapted and implemented based on behaviour-based and multi-criteria decision making MCDM approaches on an autonomous robot. The algorithms were also tested in simulation and validated by experiments performed on a real robot. According to the results, the algorithms demonstrate the ability to mitigate the unfavourable effects of the limitations. |
format | Online Article Text |
id | pubmed-6358856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63588562019-02-06 Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations Ardiny, Hadi Witwicki, Stefan Mondada, Francesco Sensors (Basel) Article Effective radioactive hotspot localization and detection is limited by sensor characteristics (i.e., the long acquisition time and poor angular resolution AR of a gamma camera) that significantly degrade the performance of autonomous exploration in terms of the completion time and accuracy. The goal of this research is to study effective exploration algorithms that take into account these specific sensor limitations. These exploration algorithms are adapted and implemented based on behaviour-based and multi-criteria decision making MCDM approaches on an autonomous robot. The algorithms were also tested in simulation and validated by experiments performed on a real robot. According to the results, the algorithms demonstrate the ability to mitigate the unfavourable effects of the limitations. MDPI 2019-01-12 /pmc/articles/PMC6358856/ /pubmed/30642085 http://dx.doi.org/10.3390/s19020292 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ardiny, Hadi Witwicki, Stefan Mondada, Francesco Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title | Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title_full | Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title_fullStr | Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title_full_unstemmed | Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title_short | Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations |
title_sort | autonomous exploration for radioactive hotspots localization taking account of sensor limitations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358856/ https://www.ncbi.nlm.nih.gov/pubmed/30642085 http://dx.doi.org/10.3390/s19020292 |
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