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UAV Mission Planning Resistant to Weather Uncertainty
Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather con...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014488/ https://www.ncbi.nlm.nih.gov/pubmed/31963338 http://dx.doi.org/10.3390/s20020515 |
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author | Thibbotuwawa, Amila Bocewicz, Grzegorz Radzki, Grzegorz Nielsen, Peter Banaszak, Zbigniew |
author_facet | Thibbotuwawa, Amila Bocewicz, Grzegorz Radzki, Grzegorz Nielsen, Peter Banaszak, Zbigniew |
author_sort | Thibbotuwawa, Amila |
collection | PubMed |
description | Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning. |
format | Online Article Text |
id | pubmed-7014488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70144882020-03-09 UAV Mission Planning Resistant to Weather Uncertainty Thibbotuwawa, Amila Bocewicz, Grzegorz Radzki, Grzegorz Nielsen, Peter Banaszak, Zbigniew Sensors (Basel) Article Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning. MDPI 2020-01-16 /pmc/articles/PMC7014488/ /pubmed/31963338 http://dx.doi.org/10.3390/s20020515 Text en © 2020 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 Thibbotuwawa, Amila Bocewicz, Grzegorz Radzki, Grzegorz Nielsen, Peter Banaszak, Zbigniew UAV Mission Planning Resistant to Weather Uncertainty |
title | UAV Mission Planning Resistant to Weather Uncertainty |
title_full | UAV Mission Planning Resistant to Weather Uncertainty |
title_fullStr | UAV Mission Planning Resistant to Weather Uncertainty |
title_full_unstemmed | UAV Mission Planning Resistant to Weather Uncertainty |
title_short | UAV Mission Planning Resistant to Weather Uncertainty |
title_sort | uav mission planning resistant to weather uncertainty |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014488/ https://www.ncbi.nlm.nih.gov/pubmed/31963338 http://dx.doi.org/10.3390/s20020515 |
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