Accession Number:

ADA583113

Title:

Real-Time Inverse Kinematics for Humans

Descriptive Note:

Conference paper

Corporate Author:

IOWA UNIV IOWA CITY

Report Date:

2004-03-15

Pagination or Media Count:

19.0

Abstract:

A general methodology and associated computational algorithm for predicting realistic postures of digital humans mannequins is presented. The basic plot for this effort is a task-based approach, where we believe that humans assume different postures for different tasks. The underlying problem is characterized by the calculation or prediction of the joint displacements of the human body in such a way to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized subject to a number of constraints. The problem is formulated as a multi-objective optimization algorithm where one or more cost functions are considered as objective functions that drive the model to a solution. The formulation is then validated against existing posture prediction algorithms and confirmed with human experimental data.

Subject Categories:

  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE