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Model Free Error Compensation for Cable-Driven Robot Based on Deep Learning with Sim2real Transfer Learning

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Informatics in Control, Automation and Robotics (ICINCO 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 793))

Abstract

The paper deals with model-free error compensation for cable-driven parallel robots based on the sim2real deep transfer learning. Particular attention is paid to simulation-based error estimation for different payloads attached to the robot end-effector and the use of the Transfer Learning approach for error compensation. This allows to reduce physical experiments with a real robot and gather sufficient data set within a reasonable time, which is required for deep learning. The obtained results were applied and validated for underactuated 4-dof (degrees of freedom) cable-driven parallel robot. Model-free Deep learning-based methods for a considerable training dataset provides better accuracy than simple linear error compensators using model-based calibration procedure. The proposed sim2real Transfer Learning method allowed to speed up the process of robotics system integration and recalibration due to the significant sample efficiency improvement.

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Acknowledgements

Work was supported by the RFBR (Russian Foundation for Basic Research) (Grant No. 19-08-01234).

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Authors and Affiliations

  1. Innopolis University, Universitetskaya St., 1, Innopolis, Tatarstan, 420500, Russia

    Aydar Akhmetzyanov, Maksim Rassabin, Alexander Maloletov, Mikhail Fadeev & Alexandr Klimchik

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  1. Aydar Akhmetzyanov
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  2. Maksim Rassabin
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  3. Alexander Maloletov
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  4. Mikhail Fadeev
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  5. Alexandr Klimchik
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Correspondence to Alexandr Klimchik .

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Editors and Affiliations

  1. Ford Research and Advanced Engineering, Dearborn, MI, USA

    Oleg Gusikhin

  2. University Paris-Est Créteil (UPEC), Créteil, France

    Kurosh Madani

  3. University of Reims Champagne-Ardenne, Reims, France

    Janan Zaytoon

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Akhmetzyanov, A., Rassabin, M., Maloletov, A., Fadeev, M., Klimchik, A. (2022). Model Free Error Compensation for Cable-Driven Robot Based on Deep Learning with Sim2real Transfer Learning. In: Gusikhin, O., Madani, K., Zaytoon, J. (eds) Informatics in Control, Automation and Robotics. ICINCO 2020. Lecture Notes in Electrical Engineering, vol 793. Springer, Cham. https://doi.org/10.1007/978-3-030-92442-3_24

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