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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7506607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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