Estimation of the axis of a screw motion from noisy data - A new method based on Plucker lines

被引:16
|
作者
Teu, Koon Kiat
Kim, Wangdo [1 ]
机构
[1] Legacy Res Ctr, Biomech Lab, Portland, OR USA
[2] Nanyang Technol Univ, Sch Mech & Prod Engn, Div Engn Mech, Singapore, Singapore
关键词
screw axis; dual vector; dual Euler angle; dual transformation matrix; FHA (finite helical axis); Plucker lines; random noise; skin movement artifacts;
D O I
10.1016/j.jbiomech.2005.09.013
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The problems of estimating the motion and orientation parameters of a body segment from two n point-set patterns are analyzed using the Nicker coordinates of a line (Plucker lines). The aim is to find algorithms less complex than those in conventional use, and thus facilitating more accurate computation of the unknown parameters. All conventional techniques use point transformation to calculate the screw axis. In this paper, we present a novel technique that directly estimates the axis of a screw motion as a Plucker line. The Plucker line can be transformed via the dual-number coordinate transformation matrix. This method is compared with Schwartz and Rozumalski [2005. A new method for estimating joint parameters from motion data. Journal of Biomechanics 38, 107-116] in simulations of random measurement errors and systematic skin movements. Simulation results indicate that the methods based on Plucker lines (Plucker line method) are superior in terms of extremely good results in the determination of the screw axis direction and position as well as a concise derivation of mathematical statements. This investigation yielded practical results, which can be used to locate the axis of a screw motion in a noisy environment. Developing the dual transformation matrix (DTM) from noisy data and determining the screw axis from a given DTM is done in a manner analogous to that for handling simple rotations. A more robust approach to solve for the dual vector associated with DTM is also addressed by using the eigenvector and the singular value decomposition. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2857 / 2862
页数:6
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