Developing feedback controllers for robots with embedded sensors is challenging and typically requires expert knowledge. As machine learning (ML) advances, the development of learning-based controllers has become more and more accessible, even to non-experts. This work presents the development of a tutorial to educate non-roboticists about ML-based sensing and control in cyber-physical systems using a soft robotic device. We demonstrated this by creating a recurrent neural network-based closed-loop force controller for a soft finger with embedded soft sensors. Our hypothesis is validated in a 2.5-hour workshop session for students with no prior knowledge of robot control. This work serves as a tutorial for participants aiming to experience and perform a general benchmark for soft robot control tasks, with little or even no expertise in robotics.


    Access

    Download


    Export, share and cite



    Title :

    Machine Learning for Soft Robot Sensing and Control: A Tutorial Study


    Contributors:
    Wang, H (author) / George Thuruthel, T (author) / Gilday, K (author) / Abdulali, A (author) / Iida, F (author)

    Publication date :

    2022-07-18


    Remarks:

    In: Proceedings of the 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS). IEEE: Coventry, UK. (2022)


    Type of media :

    Paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Tutorial: Passive radar tutorial

    Kuschel, Heiner / Cristallini, Diego / Olsen, Karl Erik | IEEE | 2019


    Tutorial

    IEEE | 2011


    Soft robot and control method thereof

    ZHANG KE / WEI HONGTAO | European Patent Office | 2022

    Free access

    A Tutorial on Microwave Photonic Filters (Tutorial)

    Capmany, J. / Ortega, B. / Pastor, D. | British Library Online Contents | 2006


    Curvature sensing of a soft robot based on conductive foam

    Grube, Malte / Seifried, Robert | BASE | 2021

    Free access