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Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion

The paper shows the simulation of the behavior of a swarm of underwater drones (AUV) diffused in a closed section of the sea and inserted from a single starting point: Based on a few essential rules, we will see how their behavior evolves and how they manage to spread throughout the area assigned to...

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Detalles Bibliográficos
Autores principales: Petritoli, Enrico, Cagnetti, Marco, Leccese, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506607/
https://www.ncbi.nlm.nih.gov/pubmed/32882926
http://dx.doi.org/10.3390/s20174950
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author Petritoli, Enrico
Cagnetti, Marco
Leccese, Fabio
author_facet Petritoli, Enrico
Cagnetti, Marco
Leccese, Fabio
author_sort Petritoli, Enrico
collection PubMed
description The paper shows the simulation of the behavior of a swarm of underwater drones (AUV) diffused in a closed section of the sea and inserted from a single starting point: Based on a few essential rules, we will see how their behavior evolves and how they manage to spread throughout the area assigned to them. In the first part of this work, after defining the design of the vehicle, we introduce our vision of the swarm, its problems, and its strengths. Later, we show how to spread a series of underwater drones with “diffused intelligence” (swarm) and its microscopic diffusion model. In the last part, we present the simulation that supports our approach to the swarm.
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spelling pubmed-75066072020-09-26 Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion Petritoli, Enrico Cagnetti, Marco Leccese, Fabio Sensors (Basel) Article The paper shows the simulation of the behavior of a swarm of underwater drones (AUV) diffused in a closed section of the sea and inserted from a single starting point: Based on a few essential rules, we will see how their behavior evolves and how they manage to spread throughout the area assigned to them. In the first part of this work, after defining the design of the vehicle, we introduce our vision of the swarm, its problems, and its strengths. Later, we show how to spread a series of underwater drones with “diffused intelligence” (swarm) and its microscopic diffusion model. In the last part, we present the simulation that supports our approach to the swarm. MDPI 2020-09-01 /pmc/articles/PMC7506607/ /pubmed/32882926 http://dx.doi.org/10.3390/s20174950 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
Petritoli, Enrico
Cagnetti, Marco
Leccese, Fabio
Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title_full Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title_fullStr Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title_full_unstemmed Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title_short Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
title_sort simulation of autonomous underwater vehicles (auvs) swarm diffusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506607/
https://www.ncbi.nlm.nih.gov/pubmed/32882926
http://dx.doi.org/10.3390/s20174950
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