Modeling and simulation of a powered exoskeleton system to aid human-robot collaborative lifting

Exoskeletons are remarkable technologies that improve human strength, reduce fatigue, and restore users' abilities. In this study, a novel physics-based optimization formulation is proposed to find the optimal control of a powered elbow exoskeleton to aid the human-robot collaborative lifting task. The threedimensional (3D) human arm model has 13 degrees of freedom (DOFs), and the 3D robot arm (Sawyer robot arm) model has 10 DOFs. The inverse dynamics optimization is utilized to find the optimal lifting motion and the optimal exoskeleton assistive torque. The 3D human arm and robot arm are modeled in Denavit-Hartenberg (DH) representation. The electromechanical dynamics of the DC motor of the exoskeleton are considered in the dynamic human-robot collaborative lifting optimization. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The human-box and robot-box interactions are characterized as a collection of grasping forces. The joint torque squares of human arm and robot arm are minimized subjected to physicsand task-based constraints. The design variables include (1) control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box; (2) control points of cubic B-splines of motor current for the exoskeleton; and (3) the discretized grasping forces during lifting. The constraints include joint angle limits for human arm and robot arm, joint torque limits for human arm, robot arm and exoskeleton, human-robot grasping positions, box balance condition, initial and final box locations, and bounds on design variables. A numerical example of lifting a 10 kg box is simulated. The nonlinear collaborative lifting optimization problem is solved using a sequential quadratic programming (SQP) method in SNOPT, and the optimal solutions are found in 136.11 seconds. The simulation reports the grasping force profiles, human arm’s joint angles, and the powered elbow exoskeleton’s torque profiles. The results reveal that the proposed optimization formulation can find the exoskeleton's optimal control and lifting strategy for the human-robot collaborative lifting task.