In this article, an $SE(3)$-constrained extended Kalman filter is proposed in continuous time as well as in a more practical continuous-discrete framework. The filter allows for the state estimation of the 6-DOF rigid body motion while accounting for measurement error statistics and using the rotation matrix instead of quaternions or other attitude parameterizations. The proposed filter differs from the recently proposed $SO(3)$-constrained attitude filter in that only a subset of the configuration states are constrained in the present filter. Its effectiveness is demonstrated in a numerical example in which its performance is compared with that of an existing $SE(3)$ estimator from the literature and a Monte Carlo simulation is carried out to provide credence to the accuracy of the proposed filter.


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    Title :

    SE(3)-Constrained Extended Kalman Filtering for Rigid Body Pose Estimation


    Contributors:


    Publication date :

    2022-06-01


    Size :

    1052577 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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