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Research Papers

Estimation of Multibody Kinematics Using Position Measurements

[+] Author and Article Information
Jenchieh Lee

Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA 90089jenchieh.lee@alumni.usc.edu

Henryk Flashner

Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA 90089

Jill L. McNitt-Gray

Departments of Kinesiology, Biomedical Engineering, and Biological Sciences, University of Southern California, Los Angeles, CA 90089

J. Comput. Nonlinear Dynam 6(3), 031001 (Dec 15, 2010) (9 pages) doi:10.1115/1.4002507 History: Received February 20, 2010; Revised August 10, 2010; Published December 15, 2010; Online December 15, 2010

A method for the estimation of kinematics of a system of rigid bodies connected by three degrees of freedom rotational joints using position measurements is introduced. In the proposed approach, system kinematics are computed from experimental measurements while preserving important physical and kinematic properties. These properties include system integrity, i.e., preserving interconnections between the bodies, and the entire system dynamic properties, namely, center of mass kinematics and its angular momentum. The computational procedure consists in solving a sequence of optimizations of appropriately formulated objective functions that incorporate the preservation of physical and kinematic properties by employing the penalty function approach. The configuration of the segment kinematics of the system is computed via a quaternion parametrization of orientation that leads to an efficient computation procedure. The sequence of optimization problems is solved using an embedded iteration process. Two studies are presented to demonstrate the performance of the proposed approach: estimations of the kinematics of a simulated three-link model and of an experimentally measured 3D motion of human body during flight phase of a jump. The results of the two studies indicate fast convergence of the algorithm to an optimal solution while accurately satisfying the imposed the constraints.

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Figures

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Figure 1

Configuration of a chain of rigid bodies

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Figure 2

Interconnection between two bodies

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Figure 3

Configuration of the three-link planar model

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Figure 4

Three-link model: system configuration and joint locations for different values of weighting coefficient at t=0.2 s

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Figure 5

Three-link model: convergence of joint gaps

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Figure 6

Three-link model: convergence of joint gap velocity and system’s angular momentum for t=0.2 s

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Figure 7

Three-link model: joint gap positions and velocities

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Figure 8

Three-link model: errors in system CM position ΔP(t), linear momentum ΔL(t), and angular momentum ΔL(t)

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Figure 9

Human body motion: model configuration and marker locations

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Figure 10

Human body motion: system configuration at t=0.03 s

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Figure 11

Human body motion: computation of joint gap positions and velocities

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Figure 12

Human body motion: errors in system CM position ΔP(t), linear momentum ΔL(t), and angular momentum ΔH(t)

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