In this paper, a strategy for linear pose estimation over a time horizon is presented. This linearization is crucial for the computationally efficient formulation of predictive and optimization-based control problems in robotics. The proposed approach is based on a truncation of the Magnus expansion for the approximation of the exponential map derivative and employs Lie algebra to represent position and orientation, allowing for a unified vectorial representation in vector form that can be integrated linearly over time, offering a convenient formulation for optimization solvers. The method shows promising results for precision and computation times.


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    Title :

    A Linearization Method Based on Lie Algebra for Pose Estimation in a Time Horizon


    Additional title:

    Springer Proceedings in Advanced Robotics



    Conference:

    International Symposium on Advances in Robot Kinematics ; 2022 ; Bilbao, Spain June 26, 2022 - June 30, 2022



    Publication date :

    2022-06-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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