Introducing Stability of Forces to the Automatic Creation of Digital Human Postures

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 group. 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 account. 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