Ffau—framework for fully autonomous uavs
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/115145 |
Resumo: | Nr. 024539 (POCI-01-0247-FEDER-024539) under grant agreement No 783221 UID/EEA/00066/2019 |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Ffau—framework for fully autonomous uavsArtificial intelligenceCollision avoidanceDeep learningDronesFrameworkMachine learningNeuronal networkResilienceUAVEarth and Planetary Sciences(all)Nr. 024539 (POCI-01-0247-FEDER-024539) under grant agreement No 783221 UID/EEA/00066/2019Unmanned Aerial Vehicles (UAVs), although hardly a new technology, have recently gained a prominent role in many industries being widely used not only among enthusiastic consumers, but also in high demanding professional situations, and will have a massive societal impact over the coming years. However, the operation of UAVs is fraught with serious safety risks, such as collisions with dynamic obstacles (birds, other UAVs, or randomly thrown objects). These collision scenarios are complex to analyze in real-time, sometimes being computationally impossible to solve with existing State of the Art (SoA) algorithms, making the use of UAVs an operational hazard and therefore significantly reducing their commercial applicability in urban environments. In this work, a conceptual framework for both stand-alone and swarm (networked) UAVs is introduced, with a focus on the architectural requirements of the collision avoidance subsystem to achieve acceptable levels of safety and reliability. The SoA principles for collision avoidance against stationary objects are reviewed and a novel approach is described, using deep learning techniques to solve the computational intensive problem of real-time collision avoidance with dynamic objects. The proposed framework includes a web-interface allowing the full control of UAVs as remote clients with a supervisor cloud-based platform. The feasibility of the proposed approach was demonstrated through experimental tests using a UAV, developed from scratch using the proposed framework. Test flight results are presented for an autonomous UAV monitored from multiple countries across the world.CTS - Centro de Tecnologia e SistemasUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasDEE - Departamento de Engenharia Electrotécnica e de ComputadoresDEE2010-A1 TelecomunicaçõesDEE2010-C1 Sistemas Digitais e PercepcionaisRUNPedro, DárioMatos-Carvalho, João P.Azevedo, FábioSacoto-Martins, RicardoBernardo, LuísCampos, LuísFonseca, José M.Mora, André2021-04-07T22:15:51Z2020-10-282020-10-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article23application/pdfhttp://hdl.handle.net/10362/115145eng2072-4292PURE: 27014899https://doi.org/10.3390/rs12213533info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:57:47Zoai:run.unl.pt:10362/115145Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:42:41.895423Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Ffau—framework for fully autonomous uavs |
title |
Ffau—framework for fully autonomous uavs |
spellingShingle |
Ffau—framework for fully autonomous uavs Pedro, Dário Artificial intelligence Collision avoidance Deep learning Drones Framework Machine learning Neuronal network Resilience UAV Earth and Planetary Sciences(all) |
title_short |
Ffau—framework for fully autonomous uavs |
title_full |
Ffau—framework for fully autonomous uavs |
title_fullStr |
Ffau—framework for fully autonomous uavs |
title_full_unstemmed |
Ffau—framework for fully autonomous uavs |
title_sort |
Ffau—framework for fully autonomous uavs |
author |
Pedro, Dário |
author_facet |
Pedro, Dário Matos-Carvalho, João P. Azevedo, Fábio Sacoto-Martins, Ricardo Bernardo, Luís Campos, Luís Fonseca, José M. Mora, André |
author_role |
author |
author2 |
Matos-Carvalho, João P. Azevedo, Fábio Sacoto-Martins, Ricardo Bernardo, Luís Campos, Luís Fonseca, José M. Mora, André |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
CTS - Centro de Tecnologia e Sistemas UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias DEE - Departamento de Engenharia Electrotécnica e de Computadores DEE2010-A1 Telecomunicações DEE2010-C1 Sistemas Digitais e Percepcionais RUN |
dc.contributor.author.fl_str_mv |
Pedro, Dário Matos-Carvalho, João P. Azevedo, Fábio Sacoto-Martins, Ricardo Bernardo, Luís Campos, Luís Fonseca, José M. Mora, André |
dc.subject.por.fl_str_mv |
Artificial intelligence Collision avoidance Deep learning Drones Framework Machine learning Neuronal network Resilience UAV Earth and Planetary Sciences(all) |
topic |
Artificial intelligence Collision avoidance Deep learning Drones Framework Machine learning Neuronal network Resilience UAV Earth and Planetary Sciences(all) |
description |
Nr. 024539 (POCI-01-0247-FEDER-024539) under grant agreement No 783221 UID/EEA/00066/2019 |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-10-28 2020-10-28T00:00:00Z 2021-04-07T22:15:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/115145 |
url |
http://hdl.handle.net/10362/115145 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2072-4292 PURE: 27014899 https://doi.org/10.3390/rs12213533 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
23 application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799138038435020800 |