Universitat Politècnica de Catalunya. CRG - Grup de Robòtica Computacional
2023-10
Nowadays, the singular value decomposition (SVD) is the standard method of choice for solving the nearest rotation matrix problem. Nevertheless, many other methods are available in the literature for the 3D case. This article reviews the most representative ones, proposes alternative ones, and presents a comparative analysis to elucidate their relative computational costs and error performances. This analysis leads to the conclusion that some algebraic closed-form methods are as robust as the SVD, but significantly faster and more accurate.
Peer Reviewed
Postprint (published version)
Article
English
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica; Numerical analysis; Rotation matrices; Quaternions; Singular value decomposition; Àlgebra lineal numèrica; Classificació AMS::65 Numerical analysis::65F Numerical linear algebra
https://onlinelibrary.wiley.com/doi/full/10.1002/nla.2492
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117509GB-I00/ES/SINTESIS DE MOVIMIENTOS ROBOTICOS OPTIMAMENTE AGILES Y GRACILES/
http://creativecommons.org/licenses/by-nc-nd/4.0/
Open Access
Attribution-NonCommercial-NoDerivatives 4.0 International
E-prints [72986]