Demonstration of locomotion with the powered prosthesis AMPRO utilizing online optimization-based control

Abstract

This demonstration presents an unimpaired subject walking with a custom built self-contained powered transfemoral prosthesis: AMPRO, which is controlled by a novel nonlinear real-time optimization based controller. To achieve the behaviors that will be demonstrated, controllers that have been successfully implemented on bipedal walking robots are translated to the prosthesis with the goal of achieving natural human-like walking while minimizing power consumption. To achieve this goal, we begin by collecting reference human locomotion data via Inertial measurement Units (IMUs). This data forms the basis for an optimization problem that generates virtual constraints for the prosthesis that provably yields walking in simulation. Utilizing methods that have proven successful in generating stable robotic locomotion, control Lyapunov function (CLF) based Quadratic Programs (QPs) are utilized to optimally track the resulting desired trajectories. The parameterization of the trajectories is determined through a combination of on-board sensing on the prosthesis together with IMU data, thereby coupling the actions of the user with the controller. Finally, impedance control is integrated into the QP yielding an optimization based control law that displays remarkable tracking and robustness, outperforming traditional PD and impedance control strategies.