Optimal Control of Spine and Shoulder Powered Exoskeletons for Squat Lifting

Abstract

Abstract In this study, a two-dimensional (2D) human skeletal model is used to predict the optimal lifting motion for the cases with and without exoskeletons using inverse dynamics optimization. The kinematics and dynamics of the human model were expressed in Denavit-Hartenberg (DH) representation. Furthermore, the electromechanical dynamics of the spine and shoulder exoskeletons’ DC motors are modeled in the lifting optimization formulation. The design variables are human joint angle profiles and exoskeleton motor current profiles. The normalized human joint torque squared is minimized subject to physical and lifting task constraints. The optimization problem was solved by the gradient-based optimizer SNOPT. The comparison of the predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles are presented between lifting tasks with and without exoskeleton assistance. The optimal torques of the exoskeletons at the spine and shoulder joints are achieved by solving the lifting optimization problem, and it is observed that the proposed method has reduced the human joint torque magnitudes due to the exoskeletons’ assistance. The peak values of the human spine and shoulder joint torque magnitudes decreased by 6.40% and 38.01% respectively, due to the exoskeleton assistance. However, human knee joint torque has slightly increased due to the extra weight of the exoskeletons.