Abstract
In this paper, artificial neural network-based cable models are developed for cable-driven parallel robots. A variety of scenarios, including the transfer learning-based ANN, are examined to predict the deflections while improving the efficiency and performance of ANN. The predicted deflections for the previously unseen poses from the same region, as well as the adjacent regions, are highly satisfactory and comparable to the results obtained by a nonlinear optimization method. In addition, ANN models could predict the deflections for poses that the nonlinear optimization methods may not.
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Notash, L. (2022). Artificial Neural Network Modelling of Cable Robots. In: Kecskeméthy, A., Parenti-Castelli, V. (eds) ROMANSY 24 - Robot Design, Dynamics and Control. ROMANSY 2022. CISM International Centre for Mechanical Sciences, vol 606. Springer, Cham. https://doi.org/10.1007/978-3-031-06409-8_32
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DOI: https://doi.org/10.1007/978-3-031-06409-8_32
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