Manikin Time; Development of the Virtual Manikin with External Root and Improved Inverse Kinematics

Abstract

Simulating manual assembly operations considering ergonomic load and clearance demands requires detailed modeling of human body kinematics and motions, as well as a tight coupling to powerful algorithms for collision-free path planning. The focus in this thesis is kinematics including balance and contact forces, and ergonomically preferable motions in free space. A typical manikin has more than 100 degrees of freedom. 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 consider ergonomics aspects and maximizing comfort when choosing one solution. The most common approach to handle both forward and inverse kinematics is building a hierarchy of joints and links where one root must be defined. A popular place to define the root is in a body part, e.g. in a foot. This leads to a two-step procedure; (i) determining if re-rooting is necessary, (ii) solving the inverse kinematic problem using the Penrose pseudoinverse. In this thesis we propose using a fixed exterior root by introducing six additional parameters positioning the lower lumbar - three rotations and three translations. This makes it possible to reposition the manikin without a series of re-rooting operations. Another important aspect is to keep the manikin, affected by internal and external forces and moments, in balance. However, by utilizing the exterior root and its added degrees of freedom it is possible to solve the balance, positioning, contact force and comfort problems simultaneously in a unified way. A manikin was implemented, and some specific test cases demonstrate the applicability of the presented method and also use randomized goals to show the generality of the solver.