TY - JOUR
T1 - A robust formulation for prediction of human running
AU - Chung, Hyun Joon
AU - Xiang, Yujiang
AU - Mathai, Anith
AU - Rahmatalla, Salam
AU - Kim, Joo
AU - Marler, Timothy
AU - Beck, Steve
AU - Yang, Jingzhou
AU - Arora, Jasbir
AU - Abdel-Malek, Karim
AU - Obusek, John
PY - 2007
Y1 - 2007
N2 - A method to simulate digital human running using an optimization-based approach is presented. The digital human is considered as a mechanical system that includes link lengths, mass moments of inertia, joint torques, and external forces. The problem is formulated as an optimization problem to determine the joint angle profiles. The kinematics analysis of the model is carried out using the Denavit-Hartenberg method. The B-spline approximation is used for discretization of the joint angle profiles, and the recursive formulation is used for the dynamic equilibrium analysis. The equations of motion thus obtained are treated as equality constraints in the optimization process. With this formulation, a method for the integration of constrained equations of motion is not required. This is a unique feature of the present formulation and has advantages for the numerical solution process. The formulation also offers considerable flexibility for simulating different running conditions quite routinely. The zero moment point (ZMP) constraint during the foot support phase is imposed in the optimization problem. The proposed approach works quite well, and several realistic simulations of human running are generated.
AB - A method to simulate digital human running using an optimization-based approach is presented. The digital human is considered as a mechanical system that includes link lengths, mass moments of inertia, joint torques, and external forces. The problem is formulated as an optimization problem to determine the joint angle profiles. The kinematics analysis of the model is carried out using the Denavit-Hartenberg method. The B-spline approximation is used for discretization of the joint angle profiles, and the recursive formulation is used for the dynamic equilibrium analysis. The equations of motion thus obtained are treated as equality constraints in the optimization process. With this formulation, a method for the integration of constrained equations of motion is not required. This is a unique feature of the present formulation and has advantages for the numerical solution process. The formulation also offers considerable flexibility for simulating different running conditions quite routinely. The zero moment point (ZMP) constraint during the foot support phase is imposed in the optimization problem. The proposed approach works quite well, and several realistic simulations of human running are generated.
UR - http://www.scopus.com/inward/record.url?scp=84902034799&partnerID=8YFLogxK
U2 - 10.4271/2007-01-2490
DO - 10.4271/2007-01-2490
M3 - Conference article
AN - SCOPUS:84902034799
SN - 0148-7191
JO - SAE Technical Papers
JF - SAE Technical Papers
T2 - Digital Human Modeling for Design and Engineering Conference and Exhibition
Y2 - 12 June 2007 through 14 June 2007
ER -