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.
A Linearization Method Based on Lie Algebra for Pose Estimation in a Time Horizon
Springer Proceedings in Advanced Robotics
International Symposium on Advances in Robot Kinematics ; 2022 ; Bilbao, Spain June 26, 2022 - June 30, 2022
2022-06-18
10 pages
Article/Chapter (Book)
Electronic Resource
English
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