Biomechanical optimal control of human arm motion

As both ordinary and well-trained human motion is mostly planned and controlled unconsciously by the central nervous system (CNS), human control mechanisms remain relatively obscure. Despite, they are an interesting topic, for example, with regard to improve protheses or athletic motion. To learn and understand more about the control of human motion, we use rigid multibody systems to represent bones and joints and formulate an optimal control problem (OCP) with the goal to minimise a physiologically motivated cost function, while the equations of motion and further nonlinear constraints have to be fulfilled. The investigated biomechanical movements are induced either via joint torques or via Hilltype muscle forces. We compare several cost functions known from literature to another one concerning the impact on the joints by involving the constraint forces. A direct transcription method called DMOCC (discrete mechanics and optimal control for constraint systems) is used to solve the OCP, whereby we benefit from its structure preserving formulation, as the resulting optimal discrete trajectories are symplectic-momentum preserving.