Control of Separable Subsystems with Application to Prostheses

Nonlinear control methodologies have successfully realized stable human-like walking on powered prostheses. However, these methods are typically restricted to model independent controllers due to the unknown human dynamics acting on the prosthesis. This paper overcomes this restriction by introducing the notion of a separable subsystem control law, independent of the full system dynamics. By constructing an equivalent subsystem, we calculate the control law with local information. We build a subsystem model of a general open-chain manipulator to demonstrate the control method's applicability. Employing these methods for an amputee-prosthesis model, we develop a model dependent prosthesis controller that relies solely on measurable states and inputs but is equivalent to a controller developed with knowledge of the human dynamics and states

Control of Separable Subsystems with Application to Prostheses

Nonlinear control methodologies have successfully realized stable human-like walking on powered prostheses. However, these methods are typically restricted to model independent controllers due to the unknown human dynamics acting on the prosthesis. This paper overcomes this restriction by introducing the notion of a separable subsystem control law, independent of the full system dynamics. By constructing an equivalent subsystem, we calculate the control law with local information. We build a subsystem model of a general open-chain manipulator to demonstrate the control method's applicability. Employing these methods for an amputee-prosthesis model, we develop a model dependent prosthesis controller that relies solely on measurable states and inputs but is equivalent to a controller developed with knowledge of the human dynamics and states.Comment: 8 pages, 6 figure

First steps toward translating robotic walking to prostheses: a nonlinear optimization based control approach

This paper presents the first steps toward successfully translating nonlinear real-time optimization based controllers from bipedal walking robots to a self-contained powered transfemoral prosthesis: AMPRO, with the goal of improving both the tracking performance and the energy efficiency of prostheses control. To achieve this goal, a novel optimization-based optimal control strategy combining control Lyapunov function based quadratic programs with impedance control is proposed. This optimization-based optimal controller is first verified on a human-like bipedal robot platform, AMBER. The results indicate improved (compared to variable impedance control) tracking performance, stability and robustness to unknown disturbances. To translate this complete methodology to a prosthetic device with an amputee, we begin by collecting reference locomotion data from a healthy subject via inertial measurement units (IMUs). This data forms the basis for an optimization problem that generates virtual constraints, i.e., parameterized trajectories, specifically for the amputee . A online optimization based controller is utilized to optimally track the resulting desired trajectories. An autonomous, state based parameterization of the trajectories is implemented through a combination of on-board sensing coupled with IMU data, thereby linking the gait progression with the actions of the user. Importantly, the proposed control law displays remarkable tracking and improved energy efficiency, outperforming PD and impedance control strategies. This is demonstrated experimentally on the prosthesis AMPRO through the implementation of a holistic sensing, algorithm and control framework, resulting in dynamic and stable prosthetic walking with a transfemoral amputee

Outputs of human walking for bipedal robotic controller design

Abstract — This paper presents a method to determine out-puts associated with human walking data that can be used to design controllers that achieve human-like robotic walking. We consider a collection of human outputs, i.e., functions of the kinematics computed from experimental human data, that satisfy criteria necessary for human-inspired bipedal robot control construction. These human outputs are described in a form amendable to controller design through a special class of time based functions—termed canonical walking functions. An optimization problem is presented to determine the parameters of this controller that yields the best fit to the human data that simultaneously produces stable robotic walking. The optimal value of the cost function is used as a metric to determine which human outputs result in the most “human-like ” robotic walking. The human-like nature of the resulting robotic walking is verified through simulation. I

Über den Einfluss der Fußgeometrie auf die Energieeffizienz beim zweibeinigen Gehen

Der Einfluss der Fußgeometrie auf die Energieeffizienz beim zweibeinigen Gehen wird untersucht. Es wird eine Methode zur Optimierung der Fußgeometrie für einen zweibeinigen Roboter entwickelt. Grundlage ist ein ebenes Modell mit beliebieger, konvexer Fußgeometrie in Kombination mit einer Regelung auf Basis der hybriden Nulldynamik. Es werden optimale Bewegungen und Fußgeometrien ermittelt. Im Vergleich zu einem Modell mit Punktfüßen ergeben sich Energieeinsparungen von über 80%