In this paper, an admittance controller based on a gray prediction model is designed for end-effector gripping force. The gray prediction model is used to predict environmental parameters in real-time and dynamically adjusts the reference position to reduce the steady-state force error. In this way, the dynamic response capability of impedance control can be improved, and its steady-state force error is also reduced. To this end, the designed method can grasp soft objects with unknown characteristics. The algorithm is validated by simulation experiments, which provide a theoretical basis for flexible fruit grasping.


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    Titel :

    Grasp Compliant Control Using Adaptive Admittance Control Methods for Flexible Objects


    Weitere Titelangaben:

    Lect.Notes Computer


    Beteiligte:
    Yang, Huayong (Herausgeber:in) / Liu, Honghai (Herausgeber:in) / Zou, Jun (Herausgeber:in) / Yin, Zhouping (Herausgeber:in) / Liu, Lianqing (Herausgeber:in) / Yang, Geng (Herausgeber:in) / Ouyang, Xiaoping (Herausgeber:in) / Wang, Zhiyong (Herausgeber:in) / Tang, Qirong (Autor:in) / Yang, Hao (Autor:in)

    Kongress:

    International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023



    Erscheinungsdatum :

    21.10.2023


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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