Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/91319
Título: | A DMPs-based approach for human-like robotic movements |
Autor(es): | Coelho, Luís Pedro Machado Cerqueira, Sara Maria Brito Araújo Martins, Vítor Hugo Brandão André, João Carlos Vieira Peixoto Santos, Cristina |
Palavras-chave: | Dynamic movement primitives Human-like movement Learning from demonstration |
Data: | Mai-2024 |
Editora: | Institute of Electrical and Electronics Engineers (IEEE) |
Resumo(s): | Industry 5.0 requires flexible and agile robots, capable to be adapted to different tasks. Tasks that demand from human workers complex movements, with large amplitudes and considerable loads, and whose layout alteration to allow good ergonomics would imply a very significant economic expenditure. In these cases, where the ergonomic safety of the workers is not guaranteed, the introduction of a robot in a production line is preferable. Human-robot collaboration pose as a solution for this problematic. However, human-likeness motion reproduction is still missing from robots. This paper explores a Learning from Demonstration strategy, a subfield of Human-Robot Collaboration (HRC) focused on teaching robots how to master a skill based on human demonstrations. Specifically, 12 human movements were recorded using MTw Awinda Motion Capture system to be further modelled by non-linear dynamical system, specifically, Dynamic Movement primitives (DMP), whose weights are learned using Covariance matrix adaptation evolution strategy (CMAES). This was used to learn how to perform human movements and transfer these skills to a collaborative Robot UR10e. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/91319 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CMEMS - Artigos em livros de atas/Papers in proceedings |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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human_like_dmp_project_icarsc2024 (1).pdf Acesso restrito! | 5,59 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons