Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/83922
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Campo DC | Valor | Idioma |
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dc.contributor.author | Boas, Ana Rita Vilas | por |
dc.contributor.author | André, João | por |
dc.contributor.author | Cerqueira, Sara Maria Brito Araújo | por |
dc.contributor.author | Santos, Cristina | por |
dc.date.accessioned | 2023-04-13T08:19:55Z | - |
dc.date.issued | 2023-04-26 | - |
dc.identifier.isbn | 979-8-3503-0121-2 | - |
dc.identifier.uri | https://hdl.handle.net/1822/83922 | - |
dc.description.abstract | Industry 5.0 places humans alongside robots on a symbiotic collaboration to improve the efficiency and productivity of industrial processes. The current manufacturing industry targets personalized products, that demand flexible, agile, and quickly changeable workstations that require less skilled workers capable to handle the different production needs. Human-robot collaboration and Learning from demonstration are emerging fields in robotics that can be exploited for this end. This paper explores a learning from demonstration (LfD) approach to learn how to perform a collaborative task with an experienced collaborator and actively teach and/or assist a novice worker. A reference trajetory was recorded using the UR10e robot and modelled by non-linear dynamical system, specifically, dynamic movement primitives (DMPs), whose weights are learned using Covariance matrix adaptation evolution strategy (CMA-ES). This paper also explores DMP effectiveness to generate the learned trajectory, with the ultimate goal of managing the quality of a collaborative task. The obtained results explore DMPs robustness against sudden perturbations and deviations from the encoded trajectory, both in simulation and in real context. Furthermore, the flexibility and stability of DMPs in learning the references’ trajectories, as well as their temporal and scale invariance, were verified. | por |
dc.description.sponsorship | This work was supported in part by the Fundac¸ao para a Ciência e Tecnologia (FCT) under the national support to RD units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020, and by the FEDER Funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI) and P2020 with the Reference Project SmartOs Grant POCI-01-0247-FEDER-039868. Sara Cerqueira was supported by the doctoral Grant SFRH/BD/151382/2021, financed by the Portuguese Foundation for Science and Technology (FCT), under MIT Portugal Program | por |
dc.language.iso | eng | por |
dc.publisher | IEEE | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04436%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04436%2F2020/PT | por |
dc.relation | POCI-01-0247-FEDER-039868 | por |
dc.relation | info:eu-repo/grantAgreement/FCT/OE/SFRH%2FBD%2F151382%2F2021/PT | por |
dc.rights | restrictedAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | por |
dc.subject | Human-robot collaboration | por |
dc.subject | Dynamic movement primitives | por |
dc.subject | Task quality | por |
dc.subject | Learning from de demonstration | por |
dc.subject | Learning from demonstration | por |
dc.title | A DMPs-based approach for human-robot collaboration task quality management | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 226 | por |
oaire.citationEndPage | 231 | por |
dc.identifier.doi | 10.1109/ICARSC58346.2023.10129609 | por |
dc.date.embargo | 10000-01-01 | - |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
sdum.conferencePublication | 2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) | por |
oaire.version | AM | por |
dc.subject.ods | Indústria, inovação e infraestruturas | por |
Aparece nas coleções: | CMEMS - Artigos em livros de atas/Papers in proceedings |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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paper_62.pdf Acesso restrito! | 3,2 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons