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Web AR Solution for UAV Pilot Training and Usability Testing

2021-02-19Artigo científico Acesso aberto
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datacite.subject.fosCiências Naturais::Ciências Físicas
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.fosCiências Naturais::Ciências Químicas
datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.fosCiências Naturais::Ciências Biológicas
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorRibeiro, Roberto
dc.contributor.authorRamos, João
dc.contributor.authorSafadinho, David
dc.contributor.authorReis, Arsénio
dc.contributor.authorRabadão, Carlos
dc.contributor.authorBarroso, João
dc.contributor.authorPereira, António
dc.date.accessioned2026-03-30T14:44:58Z
dc.date.available2026-03-30T14:44:58Z
dc.date.issued2021-02-19
dc.description.abstractData and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.eng
dc.description.sponsorshipFunding This work is financed by National Funds through the Portuguese funding agency, FCT-Fundação para a Ciência e a Tecnologia, within project UIDB/50014/2020, and was partially supported by Portuguese National funds through FITEC-Programa Interface, with reference CIT “INOV-INESC Inovação-Financiamento Base” and by Portuguese Fundação para a Ciência e a Tecnologia-FCT, I.P., under the project UIDB/04524/2020. Acknowledgments The authors acknowledge the Computer Science and Communication Research Center for the facilities granted in the implementation of part of this work, in the context of the Smart IoT Ecosystems research line and the Mobile Computing Laboratory of the School of Technology and Management of the Polytechnic of Leiria. The authors also acknowledge the authorship of some of the images used in the document, obtained in the webpages “www.flaticon.com” and “www.freepik.com”. The authors are Smashicon, Flat Icons, Freepik, Eucalyp, and Macrovector.
dc.identifier.citationRibeiro, R.; Ramos, J.; Safadinho, D.; Reis, A.; Rabadão, C.; Barroso, J.; Pereira, A.Web AR Solution for UAV Pilot Training and Usability Testing. Sensors 2021, 21, 1456. https://doi.org/10.3390/s21041456.
dc.identifier.doi10.3390/s21041456
dc.identifier.eissn1424-8220
dc.identifier.urihttp://hdl.handle.net/10400.8/16054
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
dc.relationResearch Center in Informatics and Communications
dc.relation.hasversionhttps://www.mdpi.com/1424-8220/21/4/1456
dc.relation.ispartofSensors
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectaugmented reality
dc.subjectAR obstacle courses
dc.subjecthuman–drone interaction
dc.subjectmarker-based AR
dc.subjectunmanned aerial vehicles
dc.subjectUAV control interfaces
dc.subjectUAV pilot training
dc.subjectWeb AR
dc.titleWeb AR Solution for UAV Pilot Training and Usability Testingeng
dc.typejournal article
dcterms.referenceshttps://puzzlepack.itch.io/webar-training-simulator
dspace.entity.typePublication
oaire.awardNumberUIDB/50014/2020
oaire.awardNumberUIDB/04524/2020
oaire.awardTitleINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
oaire.awardTitleResearch Center in Informatics and Communications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50014%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04524%2F2020/PT
oaire.citation.endPage30
oaire.citation.issue4
oaire.citation.startPage1
oaire.citation.titleJournal of Sensors
oaire.citation.volume21
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.affiliation.nameEng. Informática
person.familyNameRibeiro
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person.familyNameSafadinho
person.familyNameRabadão
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person.givenNameRoberto
person.givenNameJoão
person.givenNameDavid
person.givenNameCarlos
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person.identifier.ciencia-id7F12-40BA-57CD
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person.identifier.ciencia-idE215-4F0F-33EC
person.identifier.orcid0000-0003-1547-4674
person.identifier.orcid0000-0001-5361-9809
person.identifier.orcid0000-0001-5700-7893
person.identifier.orcid0000-0001-7332-4397
person.identifier.orcid0000-0001-5062-1241
person.identifier.ridM-3235-2013
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person.identifier.scopus-author-id22433497800
person.identifier.scopus-author-id7402230199
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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Data and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.
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