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Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428082/ https://www.ncbi.nlm.nih.gov/pubmed/28430120 http://dx.doi.org/10.3390/s17040918 |
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author | Ristic, Branko Angley, Daniel Moran, Bill Palmer, Jennifer L. |
author_facet | Ristic, Branko Angley, Daniel Moran, Bill Palmer, Jennifer L. |
author_sort | Ristic, Branko |
collection | PubMed |
description | Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the source parameter vector is carried out using the Rao–Blackwell dimension-reduction method, while the robots are controlled autonomously to move in a scalable formation. Estimation and control are carried out in a centralised replicated fusion architecture assuming all-to-all communication. The paper presents a comprehensive numerical analysis of the proposed algorithm, including the search-time and displacement statistics. |
format | Online Article Text |
id | pubmed-5428082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54280822017-05-12 Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment Ristic, Branko Angley, Daniel Moran, Bill Palmer, Jennifer L. Sensors (Basel) Article Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the source parameter vector is carried out using the Rao–Blackwell dimension-reduction method, while the robots are controlled autonomously to move in a scalable formation. Estimation and control are carried out in a centralised replicated fusion architecture assuming all-to-all communication. The paper presents a comprehensive numerical analysis of the proposed algorithm, including the search-time and displacement statistics. MDPI 2017-04-21 /pmc/articles/PMC5428082/ /pubmed/28430120 http://dx.doi.org/10.3390/s17040918 Text en © 2017 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 Ristic, Branko Angley, Daniel Moran, Bill Palmer, Jennifer L. Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title | Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title_full | Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title_fullStr | Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title_full_unstemmed | Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title_short | Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment |
title_sort | autonomous multi-robot search for a hazardous source in a turbulent environment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428082/ https://www.ncbi.nlm.nih.gov/pubmed/28430120 http://dx.doi.org/10.3390/s17040918 |
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