Title:
Realization of Stair Ascent and Motion Transitions on Prostheses Utilizing Optimization-Based Control and Intent Recognition
Realization of Stair Ascent and Motion Transitions on Prostheses Utilizing Optimization-Based Control and Intent Recognition
Author(s)
Zhao, Huihua
Reher, Jacob
Horn, Jonathan
Paredes, Victor
Ames, Aaron D.
Reher, Jacob
Horn, Jonathan
Paredes, Victor
Ames, Aaron D.
Advisor(s)
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
This paper presents a systematic methodology for
achieving stable locomotion behaviors on transfemoral prostheses,
together with a framework for transitioning between
these behaviors—both of which are realized experimentally on
the self-contained custom-built prosthesis AMPRO. Extending
previous results for translating robotic walking to prosthesis,
the first main contribution of this paper is the gait generation
and control development for realizing dynamic stair climbing.
This framework leads to the second main contribution of the
paper: a methodology for motion intent recognition, allowing
for natural and smooth transitions between different motion
primitives, e.g., standing, level walking, and stair climbing. The
contributions presented in this paper, including stair ascent
and transitioning between motion primitives, are verified in
simulation and realized experimentally on AMPRO. Improved
tracking and energy efficiency is seen when the online optimization
based controller is utilized for stair climbing and
the motion intent recognition algorithm successfully transitions
between motion primitives with a success rate of over 98%.
Sponsor
Date Issued
2015-08
Extent
Resource Type
Text
Resource Subtype
Proceedings