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Adaptive assistive robotics: a framework for triadic collaboration between humans and robots.
Gordon, Daniel F N; Christou, Andreas; Stouraitis, Theodoros; Gienger, Michael; Vijayakumar, Sethu.
Afiliação
  • Gordon DFN; The University of Edinburgh, Edinburgh, UK.
  • Christou A; The Alan Turing Institute, London, UK.
  • Stouraitis T; The University of Edinburgh, Edinburgh, UK.
  • Gienger M; Honda Research Institute Europe, Offenbach, Germany.
  • Vijayakumar S; Honda Research Institute Europe, Offenbach, Germany.
R Soc Open Sci ; 10(6): 221617, 2023 Jun.
Article em En | MEDLINE | ID: mdl-37388317
ABSTRACT
Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it involves close interactions and multiple actors. We propose an effective framework for optimizing the behaviour of robots and complementary assistive technologies in systems comprising a mix of human and technological agents with numerous high-level goals. The framework uses a combination of detailed biomechanical modelling and weighted multi-objective optimization to allow for the fine tuning of robot behaviours depending on the specification of the task at hand. We illustrate our framework via two case studies across assisted living and rehabilitation scenarios, and conduct simulations and experiments of triadic collaboration in practice. Our results indicate a marked benefit to the triadic approach, showing the potential to improve outcome measures for human agents in robot-assisted tasks.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article