Prosthetic Design, AMBER Lab, College Station, Texas, USA

[Airicist]

Developer - AMBER Lab (https://pr.ai/showthread.php?5421)

bipedalrobotics.com/research.html#prostheticdesign (http://www.bipedalrobotics.com/research.html#prostheticdesign)

[Airicist]

https://youtu.be/AzF5-gqtRbc

Impedance Control for Lower-Limb Prostheses

Published on Apr 27, 2013


Experimental demonstration of learned impedance control parameters for lower-limb prosthesis. The process begins through the generation of locomotion gaits with human-inspired control. This is used as a basis for learning impedance control parameters. Finally, these parameters are checked both experimentally, and through simulation.

[Airicist]

https://youtu.be/EzOIb0CP_pU

Introducing AMPRO: Translating Robotic Locomotion to Powered Transfemoral Prosthesis

Published on Oct 15, 2014


Demonstration of the translation of robotic locomotion methodologies to prosthesis on AMPRO---a powered prosthesis custom built by AMBER Lab. It features on-board power, processing and advanced robotic locomotion inspired algorithms that yield stable robotic assisted locomotion.

[Airicist]

https://youtu.be/NxJ7nMsJ63o

AMPRO: Realizing Nonlinear Controllers on Prosthesis

Published on Oct 23, 2014


This video presents a methodology for successfully translating nonlinear real-time optimization based controllers from bipedal robots to a novel custom built self-contained powered transfemoral prosthesis: AMPRO.

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, i.e., parametrized trajectories, 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. This is demonstrated experimentally on AMPRO through the implementation of the holistic sensing, algorithm and control framework, with the end result being stable and human-like walking.

[Airicist]

https://youtu.be/K6mKYrVYVwE

Multi-Contact Prosthesis Walking with AMPRO

Published on Mar 25, 2015


A multi-contact walking gait, including heel-strike and toe push-off, realized on the custom-built prosthesis AMPRO. To achieve this walking behavior, human locomotion was sensed and methods for achieving multi-contact locomotion on bipedal robots were utilized to synthesize controllers for the prosthesis.