Cargando…

A Comparison of Multiple Odor Source Localization Algorithms

There are two primary algorithms for autonomous multiple odor source localization (MOSL) in an environment with turbulent fluid flow: Independent Posteriors (IP) and Dempster–Shafer (DS) theory algorithms. Both of these algorithms use a form of occupancy grid mapping to map the probability that a gi...

Descripción completa

Detalles Bibliográficos
Autores principales: Staples, Marshall, Hugenholtz, Chris, Serrano-Ramirez, Alex, Barchyn, Thomas E., Gao, Mozhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223208/
https://www.ncbi.nlm.nih.gov/pubmed/37430713
http://dx.doi.org/10.3390/s23104799
_version_ 1785049886588141568
author Staples, Marshall
Hugenholtz, Chris
Serrano-Ramirez, Alex
Barchyn, Thomas E.
Gao, Mozhou
author_facet Staples, Marshall
Hugenholtz, Chris
Serrano-Ramirez, Alex
Barchyn, Thomas E.
Gao, Mozhou
author_sort Staples, Marshall
collection PubMed
description There are two primary algorithms for autonomous multiple odor source localization (MOSL) in an environment with turbulent fluid flow: Independent Posteriors (IP) and Dempster–Shafer (DS) theory algorithms. Both of these algorithms use a form of occupancy grid mapping to map the probability that a given location is a source. They have potential applications to assist in locating emitting sources using mobile point sensors. However, the performance and limitations of these two algorithms is currently unknown, and a better understanding of their effectiveness under various conditions is required prior to application. To address this knowledge gap, we tested the response of both algorithms to different environmental and odor search parameters. The localization performance of the algorithms was measured using the earth mover’s distance. Results indicate that the IP algorithm outperformed the DS theory algorithm by minimizing source attribution in locations where there were no sources, while correctly identifying source locations. The DS theory algorithm also identified actual sources correctly but incorrectly attributed emissions to many locations where there were no sources. These results suggest that the IP algorithm offers a more appropriate approach for solving the MOSL problem in environments with turbulent fluid flow.
format Online
Article
Text
id pubmed-10223208
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-102232082023-05-28 A Comparison of Multiple Odor Source Localization Algorithms Staples, Marshall Hugenholtz, Chris Serrano-Ramirez, Alex Barchyn, Thomas E. Gao, Mozhou Sensors (Basel) Article There are two primary algorithms for autonomous multiple odor source localization (MOSL) in an environment with turbulent fluid flow: Independent Posteriors (IP) and Dempster–Shafer (DS) theory algorithms. Both of these algorithms use a form of occupancy grid mapping to map the probability that a given location is a source. They have potential applications to assist in locating emitting sources using mobile point sensors. However, the performance and limitations of these two algorithms is currently unknown, and a better understanding of their effectiveness under various conditions is required prior to application. To address this knowledge gap, we tested the response of both algorithms to different environmental and odor search parameters. The localization performance of the algorithms was measured using the earth mover’s distance. Results indicate that the IP algorithm outperformed the DS theory algorithm by minimizing source attribution in locations where there were no sources, while correctly identifying source locations. The DS theory algorithm also identified actual sources correctly but incorrectly attributed emissions to many locations where there were no sources. These results suggest that the IP algorithm offers a more appropriate approach for solving the MOSL problem in environments with turbulent fluid flow. MDPI 2023-05-16 /pmc/articles/PMC10223208/ /pubmed/37430713 http://dx.doi.org/10.3390/s23104799 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Staples, Marshall
Hugenholtz, Chris
Serrano-Ramirez, Alex
Barchyn, Thomas E.
Gao, Mozhou
A Comparison of Multiple Odor Source Localization Algorithms
title A Comparison of Multiple Odor Source Localization Algorithms
title_full A Comparison of Multiple Odor Source Localization Algorithms
title_fullStr A Comparison of Multiple Odor Source Localization Algorithms
title_full_unstemmed A Comparison of Multiple Odor Source Localization Algorithms
title_short A Comparison of Multiple Odor Source Localization Algorithms
title_sort comparison of multiple odor source localization algorithms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223208/
https://www.ncbi.nlm.nih.gov/pubmed/37430713
http://dx.doi.org/10.3390/s23104799
work_keys_str_mv AT staplesmarshall acomparisonofmultipleodorsourcelocalizationalgorithms
AT hugenholtzchris acomparisonofmultipleodorsourcelocalizationalgorithms
AT serranoramirezalex acomparisonofmultipleodorsourcelocalizationalgorithms
AT barchynthomase acomparisonofmultipleodorsourcelocalizationalgorithms
AT gaomozhou acomparisonofmultipleodorsourcelocalizationalgorithms
AT staplesmarshall comparisonofmultipleodorsourcelocalizationalgorithms
AT hugenholtzchris comparisonofmultipleodorsourcelocalizationalgorithms
AT serranoramirezalex comparisonofmultipleodorsourcelocalizationalgorithms
AT barchynthomase comparisonofmultipleodorsourcelocalizationalgorithms
AT gaomozhou comparisonofmultipleodorsourcelocalizationalgorithms