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

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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Bibliographic Details
Main Authors: Samuel M. Youssef, MennaAllah Soliman, Mahmood A. Saleh, Mostafa A. Mousa, Mahmoud Elsamanty, Ahmed G. Radwan
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Micromachines
Subjects:
Echo State Network (ESN)
reservoir computing
Recurrent Neural Network (RNN)
Long Short-Term Memory (LSTM)
soft robotics
Soft Pneumatic Actuators (SPA)
Online Access:https://www.mdpi.com/2072-666X/13/2/216

Internet

https://www.mdpi.com/2072-666X/13/2/216

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