Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing

Detalhes bibliográficos
Autor(a) principal: Lobo, Victor
Data de Publicação: 2023
Outros Autores: Santos, Nuno Pessanha, Bernardino, Alexandre
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/151629
Resumo: Pessanha Santos, N., Lobo, V., & Bernardino, A. (2023). Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing. Drones, 7(4), 243. MDPI AG. Retrieved from http://dx.doi.org/10.3390/drones7040243
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spelling Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landingalgorithm design and analysiscomputer visionunmanned aerial vehiclemodel-based trackingmotion estimationdirectional statisticsautonomous landingControl and Systems EngineeringInformation SystemsAerospace EngineeringComputer Science ApplicationsArtificial IntelligencePessanha Santos, N., Lobo, V., & Bernardino, A. (2023). Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing. Drones, 7(4), 243. MDPI AG. Retrieved from http://dx.doi.org/10.3390/drones7040243The vast increase in the available computational capability has allowed the application of Particle-Filter (PF)-based approaches for monocular 3D-model-based tracking. These filters depend on the computation of a likelihood function that is usually unavailable and can be approximated using a similarity metric. We can use temporal filtering techniques between filter iterations to achieve better results when dealing with this suboptimal approximation, which is particularly important when dealing with the Unmanned Aerial Vehicle (UAV) model symmetry. The similarity metric evaluation time is another critical concern since we usually want a real-time implementation. We explored, tested, and compared with the same dataset two different types of PFs, (i) an Unscented Bingham Filter (UBiF) and (ii) an Unscented Bingham–Gauss Filter (UBiGaF), using pose optimization in both implementations. Using optimization steps between iterations increases the convergence capability of the filter and decreases the obtained error. A new tree-based similarity metric approach is also explored based on the Distance Transform (DT), allowing a faster evaluation of the possibilities without losing accuracy. The results showed that the obtained pose estimation error is compatible with the automatic landing requirements.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNLobo, VictorSantos, Nuno PessanhaBernardino, Alexandre2023-04-05T22:18:22Z2023-04-012023-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article25application/pdfhttp://hdl.handle.net/10362/151629eng2504-446XPURE: 57728636https://doi.org/10.3390/drones7040243info: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:RCAAP2024-03-11T05:34:05Zoai:run.unl.pt:10362/151629Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:40.174125Repositório 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 Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
title Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
spellingShingle Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
Lobo, Victor
algorithm design and analysis
computer vision
unmanned aerial vehicle
model-based tracking
motion estimation
directional statistics
autonomous landing
Control and Systems Engineering
Information Systems
Aerospace Engineering
Computer Science Applications
Artificial Intelligence
title_short Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
title_full Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
title_fullStr Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
title_full_unstemmed Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
title_sort Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing
author Lobo, Victor
author_facet Lobo, Victor
Santos, Nuno Pessanha
Bernardino, Alexandre
author_role author
author2 Santos, Nuno Pessanha
Bernardino, Alexandre
author2_role author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Lobo, Victor
Santos, Nuno Pessanha
Bernardino, Alexandre
dc.subject.por.fl_str_mv algorithm design and analysis
computer vision
unmanned aerial vehicle
model-based tracking
motion estimation
directional statistics
autonomous landing
Control and Systems Engineering
Information Systems
Aerospace Engineering
Computer Science Applications
Artificial Intelligence
topic algorithm design and analysis
computer vision
unmanned aerial vehicle
model-based tracking
motion estimation
directional statistics
autonomous landing
Control and Systems Engineering
Information Systems
Aerospace Engineering
Computer Science Applications
Artificial Intelligence
description Pessanha Santos, N., Lobo, V., & Bernardino, A. (2023). Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing. Drones, 7(4), 243. MDPI AG. Retrieved from http://dx.doi.org/10.3390/drones7040243
publishDate 2023
dc.date.none.fl_str_mv 2023-04-05T22:18:22Z
2023-04-01
2023-04-01T00:00:00Z
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/10362/151629
url http://hdl.handle.net/10362/151629
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2504-446X
PURE: 57728636
https://doi.org/10.3390/drones7040243
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 25
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
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