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Institute for Robotics and Intelligent Machines (IRIM)
Institute for Robotics and Intelligent Machines (IRIM)
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ItemMulti-Contact Locomotion on Transfemoral Prostheses via Hybrid System Models and Optimization-Based Control(Georgia Institute of Technology, 2016-03) Zhao, Huihua ; Horn, Jonathan ; Reher, Jacob ; Paredes, Victor ; Ames, Aaron D.Lower-limb prostheses provide a prime example of cyber-physical systems (CPSs) requiring the synergistic development of sensing, algorithms and controllers. With a view towards better understanding CPSs of this form, this paper presents a systematic methodology using multi-domain hybrid system models and optimization-based controllers to achieve human-like multi-contact prosthetic walking on a custom-built prosthesis: AMPRO. To achieve this goal, unimpaired human locomotion data is collected and the nominal multi-contact human gait is studied. Inspired by previous work which realized multi-contact locomotion on a bipedal robot AMBER2, a hybrid system based optimization problem utilizing the collected reference human gait as reference is utilized to formally design stable multi-contact prosthetic gaits that can be implemented on the prosthesis directly. Leveraging control methods that stabilize bipedal walking robots—control Lyapunov function based quadratic programs coupled with variable impedance control—an online optimization-based controller is formulated to realize the designed gait in both simulation and experimentally on AMPRO. Improved tracking and energy efficiency are seen when this methodology is implemented experimentally. Importantly, the resulting multi-contact prosthetic walking captures the essentials of natural human walking both kinematically and kinetically.
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ItemFirst Steps Toward Translating Robotic Walking To Prostheses: A Nonlinear Optimization Based Control Approach(Georgia Institute of Technology, 2016) Zhao, Huihua ; Horn, Jonathan ; Reher, Jacob ; Paredes, Victor ; Ames, Aaron D.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 optimal control strategy combining control Lyapunov function (CLF) based quadratic programs (QP) with impedance control is proposed. This 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 human locomotion data 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 and the prosthesis. A online optimization based controller is 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. 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 the holistic sensing, algorithm and control framework, with the end result being stable prosthetic walking by an amputee.
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ItemRealization of Stair Ascent and Motion Transitions on Prostheses Utilizing Optimization-Based Control and Intent Recognition(Georgia Institute of Technology, 2015-08) Zhao, Huihua ; Reher, Jacob ; Horn, Jonathan ; Paredes, Victor ; Ames, Aaron D.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%.
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ItemA Hybrid Systems and Optimization-Based Control Approach to Realizing Multi-Contact Locomotion on Transfemoral Prostheses(Georgia Institute of Technology, 2015) Zhao, Huihua ; Horn, Jonathan ; Reher, Jacob ; Paredes, Victor ; Ames, Aaron D.This paper presents a systematic methodology utilizing multi-domain hybrid system models and optimization based controllers to achieve human-like multi-contact prosthetic walking experimentally on a custom-built prosthesis: AMPRO. Inspired by previous work that realized multi-contact locomotion on a bipedal robot AMBER2, a hybrid system based optimization problem is proposed leveraging the framework of multi-domain hybrid systems. Utilizing a reference human gait coupled with physical constraints, the end result of this optimization problem is stable multi-contact prosthetic gaits that can be implemented on the prostheses directly. Leveraging control methods that stabilize bipedal walking robots- control Lyapunov function based quadratic programs coupled with variable impedance control-an online optimization-based controller is formulated to realize the designed gait in both simulation and experimentally on AMPRO. Improved tracking and energy efficiency are seen when this methodology is implemented experimentally. Additionally, the resulting multi-contact prosthetic walking captures the essentials of natural human walking both kinematically and kinetically.
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ItemMulti-Contact Bipedal Robotic Locomotion(Georgia Institute of Technology, 2015) Zhao, Huihua ; Herei, Ayonga ; Ma, Wen-loong ; Ames, Aaron D.This paper presents a formal framework for achieving multi-contact bipedal robotic walking, and realizes this methodology experimentally on two robotic platforms: AMBER2 and ATRIAS. Inspired by the key feature encoded in human walking— multi-contact behavior—this approach begins with the analysis of human locomotion and uses it to motivate the construction of a hybrid system model representing a multi-contact robotic walking gait. Human-inspired outputs are extracted from reference locomotion data to characterize the human model or the SLIP model, and then employed to develop the human-inspired control and an optimization problem that yields stable multi-domain walking. Through a trajectory reconstruction strategy motivated by the process that generates the walking gait, the mathematical constructions are successfully translated to the two physical robots experimentally.