The compliant nature of soft robots is appealing to a wide range of applications. However, this compliant property also poses several control challenges, e.g., how to deal with infinite degrees of freedom and highly nonlinear behaviors.

    This paper proposes a hybrid controller for a pneumatic-actuated soft robot. To this end, a model-based feedforward controller is designed and combined with a correction torque calculated via Gaussian process regression. Then, the proposed model-based and hybrid controllers are experimentally validated, and a detailed comparison between controllers is presented. Notably, the experimental results highlight the potential benefits of adding a learning approach to a model-based controller to enhance the closed-loop performance while reducing the computational load exhibited by purely learning strategies.


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    Titel :

    A Hybrid Control Approach for a Pneumatic-Actuated Soft Robot


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Piazza, Cristina (Herausgeber:in) / Capsi-Morales, Patricia (Herausgeber:in) / Figueredo, Luis (Herausgeber:in) / Keppler, Manuel (Herausgeber:in) / Schütze, Hinrich (Herausgeber:in) / Tavio y Cabrera, Emilio (Autor:in) / Santina, Cosimo Della (Autor:in) / Borja, Pablo (Autor:in)

    Kongress:

    International Workshop on Human-Friendly Robotics ; 2023 ; Munich, Germany September 20, 2023 - September 21, 2023



    Erscheinungsdatum :

    2024-03-10


    Format / Umfang :

    17 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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