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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    Title :

    Grasp Compliant Control Using Adaptive Admittance Control Methods for Flexible Objects


    Additional title:

    Lect.Notes Computer


    Contributors:
    Yang, Huayong (editor) / Liu, Honghai (editor) / Zou, Jun (editor) / Yin, Zhouping (editor) / Liu, Lianqing (editor) / Yang, Geng (editor) / Ouyang, Xiaoping (editor) / Wang, Zhiyong (editor) / Tang, Qirong (author) / Yang, Hao (author)

    Conference:

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



    Publication date :

    2023-10-21


    Size :

    11 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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