A hybrid air-sea cooperative approach combined with a swarm trajectory planning method

This work addresses the issue of ocean monitoring and clean-up of polluted zones, as well as the notion of trajectory planning and fault tolerance for semi-autonomous unmanned vehicles. A hybrid approach for unmanned aerial vehicles (UAVs) is introduced to monitor the ocean region and cooperate with...

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Main Authors: Bella Salima, Belbachir Assia, Belalem Ghalem
Format: Article
Language:English
Published: De Gruyter 2020-04-01
Series:Paladyn: Journal of Behavioral Robotics
Subjects:
uav
usv
Online Access:https://doi.org/10.1515/pjbr-2020-0006
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spelling doaj-7810b71291b440208391146235bb0c772021-10-02T19:12:27ZengDe GruyterPaladyn: Journal of Behavioral Robotics2081-48362020-04-0111111813910.1515/pjbr-2020-0006pjbr-2020-0006A hybrid air-sea cooperative approach combined with a swarm trajectory planning methodBella Salima0Belbachir Assia1Belalem Ghalem2Department of Computer Science, Faculty of Exact and Applied Sciences, Laboratoire d’Informatique d’Oran (LIO), Université Oran1, Oran, AlgeriaMechatronics Department, Polytechnic Institute of Advanced Sciences, IPSA, Ivry-sur-Seine, FranceDepartment of Computer Science, Faculty of Exact and Applied Sciences, Laboratoire d’Informatique d’Oran (LIO), Université Oran1, Oran, AlgeriaThis work addresses the issue of ocean monitoring and clean-up of polluted zones, as well as the notion of trajectory planning and fault tolerance for semi-autonomous unmanned vehicles. A hybrid approach for unmanned aerial vehicles (UAVs) is introduced to monitor the ocean region and cooperate with swarm of unmanned surface vehicles (USVs) to clean dirty zones. The paper proposes two solutions that apply to trajectory planning from the base of life to the dirty zone for swarm USVs. The first solution is performed by a modified Genetic Algorithm (GA), and the second uses a modified Ant Algorithm (AA). The proposed solutions were both implemented in the simulation with different scenarios for the dirty zone. This approach detects and reduces the pollution level in ocean zones while taking into account the problem of fault tolerance related to unmanned cleaning vehicles.https://doi.org/10.1515/pjbr-2020-0006uavusvswarmtrajectory planningfault tolerance
collection DOAJ
language English
format Article
sources DOAJ
author Bella Salima
Belbachir Assia
Belalem Ghalem
spellingShingle Bella Salima
Belbachir Assia
Belalem Ghalem
A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
Paladyn: Journal of Behavioral Robotics
uav
usv
swarm
trajectory planning
fault tolerance
author_facet Bella Salima
Belbachir Assia
Belalem Ghalem
author_sort Bella Salima
title A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
title_short A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
title_full A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
title_fullStr A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
title_full_unstemmed A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
title_sort hybrid air-sea cooperative approach combined with a swarm trajectory planning method
publisher De Gruyter
series Paladyn: Journal of Behavioral Robotics
issn 2081-4836
publishDate 2020-04-01
description This work addresses the issue of ocean monitoring and clean-up of polluted zones, as well as the notion of trajectory planning and fault tolerance for semi-autonomous unmanned vehicles. A hybrid approach for unmanned aerial vehicles (UAVs) is introduced to monitor the ocean region and cooperate with swarm of unmanned surface vehicles (USVs) to clean dirty zones. The paper proposes two solutions that apply to trajectory planning from the base of life to the dirty zone for swarm USVs. The first solution is performed by a modified Genetic Algorithm (GA), and the second uses a modified Ant Algorithm (AA). The proposed solutions were both implemented in the simulation with different scenarios for the dirty zone. This approach detects and reduces the pollution level in ocean zones while taking into account the problem of fault tolerance related to unmanned cleaning vehicles.
topic uav
usv
swarm
trajectory planning
fault tolerance
url https://doi.org/10.1515/pjbr-2020-0006
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