Introducing Stability of Forces to the Automatic Creation of Digital Human Postures
Paper in proceedings, 2013
Although the degree of automation is increasing in manufacturing industries, many assembly operations are
performed manually. To avoid injuries and to reach sustainable production of high quality, comfortable
environments for the operators are vital. Poor station layouts, poor product designs or badly chosen assembly
sequences are common sources leading to unfavorable poses and motions. To keep costs low, preventive actions
should be taken early in a project, raising the need for feasibility and ergonomics studies in virtual environments
long before physical prototypes are available.
Today, in the automotive industries, such studies are conducted to some extent. The full potential, however, is
far from reached due to limited software support in terms of capability for realistic pose prediction, motion
generation and collision avoidance. As a consequence, ergonomics studies are time consuming and are mostly
done for static poses, not for full assembly motions. Furthermore, these ergonomic studies, even though
performed by a small group of highly specialized simulation engineers, show low reproducibility within the
Effective simulation of manual assembly operations considering ergonomic load and clearance demands requires
detailed modeling of human body kinematics and motions as well as a fast and robust inverse kinematics solver.
In this paper we introduce a stability measure rewarding poses insensitive to variations in contact points and
contact forces. Normally this has been neglected and only the balance of moment and forces has been taken into
The manikin used in this work has 162 degrees of freedom and uses an exterior root. To describe operations and
facilitate motion generation, the manikin is equipped with coordinate frames attached to end-effectors like hands
and feet. The inverse kinematic problem is to find joint values such that the position and orientation of hands and
feet matches certain target frames during an assembly motion. This inverse problem leads to an underdetermined
system of equations since the number of joints exceeds the end-effectors’ constraints. Due to this redundancy
there exist a set of solutions, allowing us to pick a solution that maximizes a scalar valued comfort function.
Many objectives are included in the comfort function, for example in terms of joint angles, joint moments and
solid objects’ distance to the manikin. The proposed stability measure complements the earlier balance criterion
and is combined into the comfort function. By increasing the importance of this function the digital human
model will reposition to a more stable pose.
The digital human model will be tested on a set of challenging assembly operations taken from the automotive industry to show the effect of the stability measure.