Abstract
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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The authors acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0228).
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Podobnik, J., Munih, M., Mihelj, M. (2021). Magneto-Inertial Data Sensory Fusion Based on Jacobian Weighted-Left-Pseudoinverse. In: Lenarčič, J., Siciliano, B. (eds) Advances in Robot Kinematics 2020. ARK 2020. Springer Proceedings in Advanced Robotics, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-50975-0_22
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DOI: https://doi.org/10.1007/978-3-030-50975-0_22
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