Unmanned air vehicle path planning for maritime surveillance using Cluster-base method

This paper discusses a method to determine the operation route for unmanned aerial vehicles for maritime surveillance. It is well known that there are several methods to make an aircraft path planning for ground related missions. On the other hand, path planning for maritime purposes is unnoticeabl...

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Autores principales:	Prasetyo Ardi Probo Suseno, Try Kusuma Wardana
Formato:	article
Lenguaje:	EN
Publicado:	Vilnius Gediminas Technical University 2021
Materias:	UAV path planning surveillance maritime clustering TSP Motor vehicles. Aeronautics. Astronautics TL1-4050
Acceso en línea:	https://doaj.org/article/e49fee231fda4b1d9ccc9a0c9e0cd4ba
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id	oai:doaj.org-article:e49fee231fda4b1d9ccc9a0c9e0cd4ba
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spelling	oai:doaj.org-article:e49fee231fda4b1d9ccc9a0c9e0cd4ba2021-11-25T14:49:09ZUnmanned air vehicle path planning for maritime surveillance using Cluster-base method10.3846/aviation.2021.142161648-77881822-4180https://doaj.org/article/e49fee231fda4b1d9ccc9a0c9e0cd4ba2021-11-01T00:00:00Zhttps://journals.vgtu.lt/index.php/Aviation/article/view/14216https://doaj.org/toc/1648-7788https://doaj.org/toc/1822-4180 This paper discusses a method to determine the operation route for unmanned aerial vehicles for maritime surveillance. It is well known that there are several methods to make an aircraft path planning for ground related missions. On the other hand, path planning for maritime purposes is unnoticeable. The major problem of path planning for maritime is the abundant number of nodes which can make the route becomes quite long. Hence, reducing the number of nodes is necessary to rectify this problem. The main method is to separate the surveillance area into a smaller area of operation using clustering methods and then analyze the vulnerable area using the database to create an optimum flight path in each operation area. Although this paper specifically addresses a maritime-related mission, the path planning procedures can be applied to other missions as well. In this research, the input is given from satellite recorded data. Natuna Sea is chosen as the main discussion as the Natuna Sea currently is one of the most vulnerable regions in Indonesia for illegal fishing activity. The result shows that the aircraft path able to cover most of the vulnerable areas while optimizing the route distance. Prasetyo Ardi Probo SusenoTry Kusuma WardanaVilnius Gediminas Technical UniversityarticleUAVpath planningsurveillancemaritimeclusteringTSPMotor vehicles. Aeronautics. AstronauticsTL1-4050ENAviation, Vol 25, Iss 3 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	UAV path planning surveillance maritime clustering TSP Motor vehicles. Aeronautics. Astronautics TL1-4050
spellingShingle	UAV path planning surveillance maritime clustering TSP Motor vehicles. Aeronautics. Astronautics TL1-4050 Prasetyo Ardi Probo Suseno Try Kusuma Wardana Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
description	This paper discusses a method to determine the operation route for unmanned aerial vehicles for maritime surveillance. It is well known that there are several methods to make an aircraft path planning for ground related missions. On the other hand, path planning for maritime purposes is unnoticeable. The major problem of path planning for maritime is the abundant number of nodes which can make the route becomes quite long. Hence, reducing the number of nodes is necessary to rectify this problem. The main method is to separate the surveillance area into a smaller area of operation using clustering methods and then analyze the vulnerable area using the database to create an optimum flight path in each operation area. Although this paper specifically addresses a maritime-related mission, the path planning procedures can be applied to other missions as well. In this research, the input is given from satellite recorded data. Natuna Sea is chosen as the main discussion as the Natuna Sea currently is one of the most vulnerable regions in Indonesia for illegal fishing activity. The result shows that the aircraft path able to cover most of the vulnerable areas while optimizing the route distance.
format	article
author	Prasetyo Ardi Probo Suseno Try Kusuma Wardana
author_facet	Prasetyo Ardi Probo Suseno Try Kusuma Wardana
author_sort	Prasetyo Ardi Probo Suseno
title	Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
title_short	Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
title_full	Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
title_fullStr	Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
title_full_unstemmed	Unmanned air vehicle path planning for maritime surveillance using Cluster-base method
title_sort	unmanned air vehicle path planning for maritime surveillance using cluster-base method
publisher	Vilnius Gediminas Technical University
publishDate	2021
url	https://doaj.org/article/e49fee231fda4b1d9ccc9a0c9e0cd4ba
work_keys_str_mv	AT prasetyoardiprobosuseno unmannedairvehiclepathplanningformaritimesurveillanceusingclusterbasemethod AT trykusumawardana unmannedairvehiclepathplanningformaritimesurveillanceusingclusterbasemethod
_version_	1718413412195631104

Unmanned air vehicle path planning for maritime surveillance using Cluster-base method

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