Dynamic Optimization of Human Running With Analytical Gradients

被引：10

作者：

Chung, Hyun-Joon ^{[1
]}

Arora, Jasbir S. ^{[1
]}

Abdel-Malek, Karim ^{[1
]}

Xiang, Yujiang ^{[2
]}

机构：

[1] Univ Iowa, CCAD, Iowa City, IA 52242 USA

[2] Univ Alaska Fairbanks, Dept Mech Engn, Fairbanks, AK 99775 USA

来源：

JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS | 2015年 / 10卷 / 02期

关键词：

running; recursive Lagrangian dynamics; sensitivity; impulse; arm swing; predictive dynamics; HUMAN WALKING; PATTERN GENERATION; FORCES; BIOMECHANICS; PREDICTION; SUPPORT; ROBOT;

D O I：

10.1115/1.4027672

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The optimization-based dynamic prediction of 3D human running motion is studied in this paper. A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. Recursive Lagrangian dynamics with analytical gradients for all the constraints and objective function are incorporated in the optimization process. The dynamic effort is used as the performance measure, and the impulse at the foot strike is also included in the performance measure. The joint angle profiles and joint torque profiles are calculated for the full-body human model, and the ground reaction force (GRF) is determined. Several cause-and-effect cases are studied, and the formulation for upper-body yawing motion is proposed and simulated. Simulation results from this methodology show good correlation with experimental data obtained from human subjects and the existing literature.

引用

页数：18

共 46 条

[11]

Chung H. J., 2009, THESIS U IOWA IOWA C

[12] A DYNAMIC OPTIMIZATION TECHNIQUE FOR PREDICTING MUSCLE FORCES IN THE SWING PHASE OF GAIT [J].