In this paper, the inverse kinematical analysis problem is investigated for a class of bio-inspired cable-driven robotic manipulator. Moreover, the modeling of the redundant cable-driven robotic manipulator is performed. In particular, the RBF neural network is adopted to deal with the unmodeled parameters uncertainties such that the inverse kinematic analysis precision can be improved. In the end, an illustrative example is presented for showing the usefulness of the developed analysis approach.


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    Title :

    Neural-based Inverse Kinematical Analysis for Bio-inspired Cable-driven Robotic Manipulator


    Contributors:
    Fu, Hang (author) / Liu, Yang (author) / Wu, Wei (author) / Li, Xiaoqing (author)


    Publication date :

    2020-09-28


    Size :

    875385 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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