Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data

Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning...

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Detalles Bibliográficos
Autores principales: Youssef, Samuel M., Soliman, MennaAllah, Saleh, Mahmood A., Mousa, Mostafa A., Elsamanty, Mahmoud, Radwan, Ahmed G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880441/
https://www.ncbi.nlm.nih.gov/pubmed/35208339
http://dx.doi.org/10.3390/mi13020216

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880441/
https://www.ncbi.nlm.nih.gov/pubmed/35208339
http://dx.doi.org/10.3390/mi13020216

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