Realistic Posture Prediction for Maximum Dexterity Digital Humans Laboratory, Department of Mechanical Engineering, Center for Computer Aided Design, The University of Iowa

Format:

Conference/Event

Author/Creator:

Abdel-Malek, Karim, author.

Conference Name:

Digital Human Modeling For Design And Engineering Conference And Exhibition (2001-06-26 : Arlington, Virginia, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2001

Summary:

This paper presents an efficient numerical formulation for the prediction of realistic postures. This problem is defined by the method (or procedure) used to predict the posture of a human, given a point in the reachable space. The exposition addresses (1) the determination whether a point is reachable (id est, does is it exist within the reach envelope) and (2) the calculation of a posture for a given point. While many researchers have used either statistical models of empirical data or the traditional geometric inverse kinematics method for posture prediction, we present a method based on kinematics for modeling, but one that uses optimization of a cost function to predict a realistic posture. It is shown that this method replicates the human mind in selecting a posture from an infinite number of possible postures. We illustrate the methodology and an accompanying experimental code through a planar and a spatial example, and validation using commercial human modeling and simulation code

Notes:

Vendor supplied data

Publisher Number:

2001-01-2110

Access Restriction:

Restricted for use by site license