This paper aims to study the gait estimation problem of lower limb rehabilitation exoskeleton robot, and proposes a gait estimation strategy based on covariance inter-section (CI) fusion. First, the discrete mathematical model of exoskeleton rehabilitation robot is obtained by Lagrange system discretization principle. Then, two groups of angle sensors with unavoidable measurement errors are employed to obtain the joint angles of the exoskeleton robot, and the gait of the robot is estimated by CI fusion filtering algorithm. Finally, simulation experiments show that CI fusion filtering algorithm can effectively overcome the interference of process noise, and greatly improve the accuracy of gait estimation during gait tracking.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Covariance Intersection Fusion Approach for Gait Estimation of Lower Limb Rehabilitation Exoskeleton Robot


    Contributors:
    Zhou, Yuan (author) / Hu, Zhongyao (author) / Sun, Zhe (author) / Wang, Tian (author) / Chen, Bo (author)


    Publication date :

    2022-04-08


    Size :

    964623 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Muiti-objective Gait Optimizntion of Lower-limb Exoskeleton Robot

    Ren, Hao / Shang, Wanfeng / Li, Niannian et al. | IEEE | 2020


    An adaptive gait learning strategy for lower limb exoskeleton robot

    Chen, Chunjie / Liu, Duxin / Wang, Xuesong et al. | IEEE | 2017



    Human Gait Prediction for Lower Limb Rehabilitation Exoskeleton Using Gated Recurrent Units

    Wang, Yan / Li, Zhikang / Chen, Yuguo et al. | Springer Verlag | 2021


    Feedback Linearization Control of Lower Limb Exoskeleton Robot for Rehabilitation

    Arsalan Muhammad / Rehaman Saad ur / Umair Muhammad et al. | DOAJ | 2023

    Free access