This paper presents a method for sensory fusion of magneto-inertial data for estimation of joint angles of serial kinematic chain with rotational degrees-of-freedom. Method is named Magneto-Inertial tracking based on JAcobian PseudoInverse (MIJAPI). Method incorporates a kinematic model of the mechanism and the estimation relies on the inverse kinematics solution based on the Jacobian inverse utilizing the Moore-Penrose weighted left pseudoinverse of the mechanism. Jacobian matrix is used to solve an overdetermined system in a least squares approach due to available redundant measurements resulting from constraints related to attachments of magneto-inertial sensors and kinematic model.


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    Title :

    Magneto-Inertial Data Sensory Fusion Based on Jacobian Weighted-Left-Pseudoinverse


    Additional title:

    Springer Proceedings in Advanced Robotics


    Contributors:

    Conference:

    International Symposium on Advances in Robot Kinematics ; 2020 ; Ljubljana, Slovenia December 06, 2020 - December 10, 2020



    Publication date :

    2020-07-18


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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