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Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction
A swarm of unmanned aerial vehicles (UAVs) can be used for many applications, including disaster relief, search and rescue, and establishing communication networks, due to its mobility, scalability, and robustness to failure. However, a UAV swarm’s performance is typically limited by each agent’s st...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046385/ https://www.ncbi.nlm.nih.gov/pubmed/36975354 http://dx.doi.org/10.3390/biomimetics8010124 |
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author | Pooley, Adam Gao, Max Sharma, Arushi Barnaby, Sachi Gu, Yu Gross, Jason |
author_facet | Pooley, Adam Gao, Max Sharma, Arushi Barnaby, Sachi Gu, Yu Gross, Jason |
author_sort | Pooley, Adam |
collection | PubMed |
description | A swarm of unmanned aerial vehicles (UAVs) can be used for many applications, including disaster relief, search and rescue, and establishing communication networks, due to its mobility, scalability, and robustness to failure. However, a UAV swarm’s performance is typically limited by each agent’s stored energy. Recent works have considered the usage of thermals, or vertical updrafts of warm air, to address this issue. One challenge lies in a swarm of UAVs detecting and taking advantage of these thermals. Inspired by hawks, a swarm could take advantage of thermals better than individuals due to the swarm’s distributed sensing abilities. To determine which emergent behaviors increase survival time, simulation software was created to test the behavioral models of UAV gliders around thermals. For simplicity and robustness, agents operate with limited information about other agents. The UAVs’ motion was implemented as a Boids model, replicating the behavior of flocking birds through cohesion, separation, and alignment forces. Agents equipped with a modified behavioral model exhibit dynamic flocking behavior, including relative ascension-based cohesion and relative height-based separation and alignment. The simulation results show the agents flocking to thermals and improving swarm survival. These findings present a promising method to extend the flight time of autonomous UAV swarms. |
format | Online Article Text |
id | pubmed-10046385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100463852023-03-29 Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction Pooley, Adam Gao, Max Sharma, Arushi Barnaby, Sachi Gu, Yu Gross, Jason Biomimetics (Basel) Article A swarm of unmanned aerial vehicles (UAVs) can be used for many applications, including disaster relief, search and rescue, and establishing communication networks, due to its mobility, scalability, and robustness to failure. However, a UAV swarm’s performance is typically limited by each agent’s stored energy. Recent works have considered the usage of thermals, or vertical updrafts of warm air, to address this issue. One challenge lies in a swarm of UAVs detecting and taking advantage of these thermals. Inspired by hawks, a swarm could take advantage of thermals better than individuals due to the swarm’s distributed sensing abilities. To determine which emergent behaviors increase survival time, simulation software was created to test the behavioral models of UAV gliders around thermals. For simplicity and robustness, agents operate with limited information about other agents. The UAVs’ motion was implemented as a Boids model, replicating the behavior of flocking birds through cohesion, separation, and alignment forces. Agents equipped with a modified behavioral model exhibit dynamic flocking behavior, including relative ascension-based cohesion and relative height-based separation and alignment. The simulation results show the agents flocking to thermals and improving swarm survival. These findings present a promising method to extend the flight time of autonomous UAV swarms. MDPI 2023-03-17 /pmc/articles/PMC10046385/ /pubmed/36975354 http://dx.doi.org/10.3390/biomimetics8010124 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pooley, Adam Gao, Max Sharma, Arushi Barnaby, Sachi Gu, Yu Gross, Jason Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title | Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title_full | Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title_fullStr | Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title_full_unstemmed | Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title_short | Analysis of UAV Thermal Soaring via Hawk-Inspired Swarm Interaction |
title_sort | analysis of uav thermal soaring via hawk-inspired swarm interaction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046385/ https://www.ncbi.nlm.nih.gov/pubmed/36975354 http://dx.doi.org/10.3390/biomimetics8010124 |
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