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High-altitude vertical wind profile estimation using multirotor vehicles
Capturing vertical profiles of the atmosphere and measuring wind conditions can be of significant value for weather forecasting and pollution monitoring however, collecting such data can be limited by current approaches using balloon-based radiosondes and expensive ground-based sensors. Multirotor v...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020538/ https://www.ncbi.nlm.nih.gov/pubmed/36936410 http://dx.doi.org/10.3389/frobt.2023.1112889 |
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author | McConville, Alexander Richardson, Thomas |
author_facet | McConville, Alexander Richardson, Thomas |
author_sort | McConville, Alexander |
collection | PubMed |
description | Capturing vertical profiles of the atmosphere and measuring wind conditions can be of significant value for weather forecasting and pollution monitoring however, collecting such data can be limited by current approaches using balloon-based radiosondes and expensive ground-based sensors. Multirotor vehicles can be significantly affected by the local wind conditions, and due to their under-actuated nature, the response to the flow is visible in the changes in the orientation. From these changes in orientation, wind speed and direction estimates can be determined, allowing accurate estimation with no additional sensors. In this work, we expand on and improve this method of wind speed and direction estimation and incorporate corrections for climbing flight to improve estimation during vertical profiling. These corrections were validated against sonic anemometer data before being used to gather vertical profiles of the wind conditions around Volcan De Fuego in Guatemala up to altitudes of 3000 m Above Ground Level (AGL). From the results of this work, we show we can improve the accuracy of multirotor wind estimation in vertical profiling through our improved model and some of the practical limitations of radiosondes that can be overcome through the use of UAS in this application. |
format | Online Article Text |
id | pubmed-10020538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100205382023-03-18 High-altitude vertical wind profile estimation using multirotor vehicles McConville, Alexander Richardson, Thomas Front Robot AI Robotics and AI Capturing vertical profiles of the atmosphere and measuring wind conditions can be of significant value for weather forecasting and pollution monitoring however, collecting such data can be limited by current approaches using balloon-based radiosondes and expensive ground-based sensors. Multirotor vehicles can be significantly affected by the local wind conditions, and due to their under-actuated nature, the response to the flow is visible in the changes in the orientation. From these changes in orientation, wind speed and direction estimates can be determined, allowing accurate estimation with no additional sensors. In this work, we expand on and improve this method of wind speed and direction estimation and incorporate corrections for climbing flight to improve estimation during vertical profiling. These corrections were validated against sonic anemometer data before being used to gather vertical profiles of the wind conditions around Volcan De Fuego in Guatemala up to altitudes of 3000 m Above Ground Level (AGL). From the results of this work, we show we can improve the accuracy of multirotor wind estimation in vertical profiling through our improved model and some of the practical limitations of radiosondes that can be overcome through the use of UAS in this application. Frontiers Media S.A. 2023-03-03 /pmc/articles/PMC10020538/ /pubmed/36936410 http://dx.doi.org/10.3389/frobt.2023.1112889 Text en Copyright © 2023 McConville and Richardson. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI McConville, Alexander Richardson, Thomas High-altitude vertical wind profile estimation using multirotor vehicles |
title | High-altitude vertical wind profile estimation using multirotor vehicles |
title_full | High-altitude vertical wind profile estimation using multirotor vehicles |
title_fullStr | High-altitude vertical wind profile estimation using multirotor vehicles |
title_full_unstemmed | High-altitude vertical wind profile estimation using multirotor vehicles |
title_short | High-altitude vertical wind profile estimation using multirotor vehicles |
title_sort | high-altitude vertical wind profile estimation using multirotor vehicles |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020538/ https://www.ncbi.nlm.nih.gov/pubmed/36936410 http://dx.doi.org/10.3389/frobt.2023.1112889 |
work_keys_str_mv | AT mcconvillealexander highaltitudeverticalwindprofileestimationusingmultirotorvehicles AT richardsonthomas highaltitudeverticalwindprofileestimationusingmultirotorvehicles |