Cargando…

Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework

Olfactory navigation is defined as a task of a self-propelled navigator with some sensors capabilities to detect odor (or scalar concentration) convected and diffused in a windy environment. Known for their expertise in locating an odor source, male moths feature a bio-inspirational model of olfacto...

Descripción completa

Detalles Bibliográficos
Autores principales: Golov, Yiftach, Benelli, Noam, Gurka, Roi, Harari, Ally, Zilman, Gregory, Liberzon, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720835/
https://www.ncbi.nlm.nih.gov/pubmed/35004194
http://dx.doi.org/10.1016/j.mex.2021.101529
_version_ 1784625208665047040
author Golov, Yiftach
Benelli, Noam
Gurka, Roi
Harari, Ally
Zilman, Gregory
Liberzon, Alex
author_facet Golov, Yiftach
Benelli, Noam
Gurka, Roi
Harari, Ally
Zilman, Gregory
Liberzon, Alex
author_sort Golov, Yiftach
collection PubMed
description Olfactory navigation is defined as a task of a self-propelled navigator with some sensors capabilities to detect odor (or scalar concentration) convected and diffused in a windy environment. Known for their expertise in locating an odor source, male moths feature a bio-inspirational model of olfactory navigation using chemosensory. Many studies have developed moths-inspired algorithms based on proposed strategies of odor-sourcing. However, comparing among various bio-inspired strategies is challenging, due to the lack of a componential framework that allows statistical comparison of their performances, in a controlled environment. This work aims at closing this gap, using an open source, freely accessible simulation framework. To demonstrate the applicability of our simulated framework as a benchmarking tool, we implemented two different moth-inspired navigation strategies; for each strategy, specific modifications in the navigation module were carried out, resulting in four different navigation models. We tested the performance of moth-like navigators of these models through various wind and odor spread parameters in a virtual turbulent environment. The performance of the navigators was comprehensively analyzed using bio-statistical tests. This benchmark-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting in deducing the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments. • The open-source framework `Mothpy' provides a computational platform that simulates the behavior of moth-like navigators, using two main inputs to be modified by the user: (1) flow condition; and (2) navigation strategy. • `Mothpy' can be used as a benchmarking platform to compare the performance of multiple moth-like navigators, under various physical environments, and different searching strategies. • Method name: Mothpy 0.0.1' - an open-source moth-inspired navigator simulator.
format Online
Article
Text
id pubmed-8720835
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-87208352022-01-07 Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework Golov, Yiftach Benelli, Noam Gurka, Roi Harari, Ally Zilman, Gregory Liberzon, Alex MethodsX Method Article Olfactory navigation is defined as a task of a self-propelled navigator with some sensors capabilities to detect odor (or scalar concentration) convected and diffused in a windy environment. Known for their expertise in locating an odor source, male moths feature a bio-inspirational model of olfactory navigation using chemosensory. Many studies have developed moths-inspired algorithms based on proposed strategies of odor-sourcing. However, comparing among various bio-inspired strategies is challenging, due to the lack of a componential framework that allows statistical comparison of their performances, in a controlled environment. This work aims at closing this gap, using an open source, freely accessible simulation framework. To demonstrate the applicability of our simulated framework as a benchmarking tool, we implemented two different moth-inspired navigation strategies; for each strategy, specific modifications in the navigation module were carried out, resulting in four different navigation models. We tested the performance of moth-like navigators of these models through various wind and odor spread parameters in a virtual turbulent environment. The performance of the navigators was comprehensively analyzed using bio-statistical tests. This benchmark-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting in deducing the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments. • The open-source framework `Mothpy' provides a computational platform that simulates the behavior of moth-like navigators, using two main inputs to be modified by the user: (1) flow condition; and (2) navigation strategy. • `Mothpy' can be used as a benchmarking platform to compare the performance of multiple moth-like navigators, under various physical environments, and different searching strategies. • Method name: Mothpy 0.0.1' - an open-source moth-inspired navigator simulator. Elsevier 2021-09-27 /pmc/articles/PMC8720835/ /pubmed/35004194 http://dx.doi.org/10.1016/j.mex.2021.101529 Text en © 2021 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Golov, Yiftach
Benelli, Noam
Gurka, Roi
Harari, Ally
Zilman, Gregory
Liberzon, Alex
Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title_full Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title_fullStr Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title_full_unstemmed Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title_short Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework
title_sort open-source computational simulation of moth-inspired navigation algorithm: a benchmark framework
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720835/
https://www.ncbi.nlm.nih.gov/pubmed/35004194
http://dx.doi.org/10.1016/j.mex.2021.101529
work_keys_str_mv AT golovyiftach opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework
AT benellinoam opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework
AT gurkaroi opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework
AT hararially opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework
AT zilmangregory opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework
AT liberzonalex opensourcecomputationalsimulationofmothinspirednavigationalgorithmabenchmarkframework