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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Online Access: | https://doi.org/10.1515/pjbr-2020-0006 |
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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 |
work_keys_str_mv |
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