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Self-organized Learning from Synthetic and Real-World Data for a Humanoid Exercise Robot
We propose a neural learning approach for a humanoid exercise robot that can automatically analyze and correct physical exercises. Such an exercise robot should be able to train many different human partners over time and thus requires the ability for lifelong learning. To this end, we develop a mod...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585214/ https://www.ncbi.nlm.nih.gov/pubmed/36274912 http://dx.doi.org/10.3389/frobt.2022.669719 |