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Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind

In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wi...

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Detalles Bibliográficos
Autores principales: Coombes, Matthew, Fletcher, Tom, Chen, Wen-Hua, Liu, Cunjia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068989/
https://www.ncbi.nlm.nih.gov/pubmed/29970818
http://dx.doi.org/10.3390/s18072132
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author Coombes, Matthew
Fletcher, Tom
Chen, Wen-Hua
Liu, Cunjia
author_facet Coombes, Matthew
Fletcher, Tom
Chen, Wen-Hua
Liu, Cunjia
author_sort Coombes, Matthew
collection PubMed
description In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wing aircraft surveys. This is achieved threefold: by the addition of wind to the survey flight time model, accounting for the fact fixed-wing aircraft are not constrained to flight within the polygon of the region of interest, and an intelligent method for decomposing the region into convex polygons conducive to quick flight times. It is shown that wind can make a huge difference to survey time, and that flying perpendicular can confer a flight time advantage. Small UAVs, which have very slow airspeeds, can very easily be flying in wind, which is 50% of their airspeed. This is why the technique is shown to be so effective, due to the fact that ignoring wind for small, slow, fixed-wing aircraft is a considerable oversight. Comparing this method to previous techniques using a Monte Carlo simulation on randomised polygons shows a significant reduction in flight time.
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spelling pubmed-60689892018-08-07 Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind Coombes, Matthew Fletcher, Tom Chen, Wen-Hua Liu, Cunjia Sensors (Basel) Article In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wing aircraft surveys. This is achieved threefold: by the addition of wind to the survey flight time model, accounting for the fact fixed-wing aircraft are not constrained to flight within the polygon of the region of interest, and an intelligent method for decomposing the region into convex polygons conducive to quick flight times. It is shown that wind can make a huge difference to survey time, and that flying perpendicular can confer a flight time advantage. Small UAVs, which have very slow airspeeds, can very easily be flying in wind, which is 50% of their airspeed. This is why the technique is shown to be so effective, due to the fact that ignoring wind for small, slow, fixed-wing aircraft is a considerable oversight. Comparing this method to previous techniques using a Monte Carlo simulation on randomised polygons shows a significant reduction in flight time. MDPI 2018-07-03 /pmc/articles/PMC6068989/ /pubmed/29970818 http://dx.doi.org/10.3390/s18072132 Text en © 2018 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
Coombes, Matthew
Fletcher, Tom
Chen, Wen-Hua
Liu, Cunjia
Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title_full Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title_fullStr Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title_full_unstemmed Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title_short Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
title_sort optimal polygon decomposition for uav survey coverage path planning in wind
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068989/
https://www.ncbi.nlm.nih.gov/pubmed/29970818
http://dx.doi.org/10.3390/s18072132
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