Biomechanically-based motion control for a digital human

Abstract

An algorithm for both human-like motion generation and joint torques computation for digital humans is addressed in this paper. This goal has been achieved using techniques derived from robotics. In particular, the so-called augmented Jacobian has been used to solve the inverse kinematics problem with a single closed loop inverse kinematics algorithm. Furthermore, a position control for the center of mass of the kinematic chain, and for its projection on the support plane (center of pressure), has been implemented to achieve easy posture control. Thus, the inverse kinematics can be solved taking into account the static balance of the digital human. Moreover, the proposed algorithm allows simulating quite complex tasks, which involve the motion of the whole body, by means of only few task-related control points arbitrary located on the whole kinematic chain. The resulting movements are quite natural even for complex tasks as can be seen on the simulation experiments reported which show the effectiveness of the proposed approach. Finally, the joint torques can be computed thanks to the kinetostatics duality: the results are in accordance with biomechanical analyses

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