Data Structures and Algorithms

   

Robust Quaternion Estimation with Geometric Algebra

Authors: Mauricio Cele Lopez Belon

Robust methods for finding the best rotation aligning two sets of corresponding vectors are formulated in the linear algebra framework, using tools like the SVD for polar decomposition or QR for finding eigenvectors. Those are well established numerical algorithms which on the other hand are iterative and computationally expensive. Recently, closed form solutions has been proposed in the quaternion’s framework, those methods are fast but they have singularities i.e., they completely fail on certain input data. In this paper we propose a robust attitude estimator based on a formulation of the problem in Geometric Algebra. We find the optimal eigen-quaternion in closed form with high accuracy and with competitive performance respect to the fastest methods reported in literature.

Comments: 11 Pages. Submitted to Advances in Applied Clifford Algebras

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Submission history

[v1] 2019-11-07 02:38:29

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