Outputs of human walking for bipedal robotic controller design

Jiang, Shengyuan; Partrick, Shawanee; Zhao, Huihua; Ames, Aaron D.

doi:10.1109/acc.2012.6315648

Cited by 18 publications

(15 citation statements)

References 21 publications

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“…To express the segment estimation in terms of the available joint mobility of AMPRO, the measurements from the IMUs are projected onto the saggital plane at each time step before they are passed to the filter. Additionally, we assume that the forward velocity of the hip is constant [21], [22] and that sinusoidal movement of the hip in the vertical direction will yield negligible acceleration in comparison to walking dynamics. An EKF is instantiated for each segment in the model and updated sequentially along the kinematic chain from the hip.…”

Section: Motion Capture With Imumentioning

confidence: 99%

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

et al. 2016

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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 uti

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Section: Motion Capture With Imumentioning

confidence: 99%

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

et al. 2016

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“…Additionally, from analysis of multicontact human locomotion data, the linearized forward hip position, , was discovered to increase linearly, i.e., the hip velocity is approximately constant through the progress of a step cycle [23]. This motivates the following phase variable: (4) aiming to remove the dependency of time [6], [36].…”

Section: B Human-inspired Outputsmentioning

confidence: 97%

Multicontact Locomotion on Transfemoral Prostheses via Hybrid System Models and Optimization-Based Control

Zhao

Horn

Reher

et al. 2016

IEEE Trans. Automat. Sci. Eng.

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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 multidomain hybrid system models and optimization-based controllers to achieve human-like multicontact prosthetic walking on a custom-built prosthesis: AMPRO. To achieve this goal, unimpaired human locomotion data is collected and the nominal multicontact human gait is studied. Inspired by previous work which realized multicontact locomotion on the bipedal robot AMBER2, a hybrid system-based optimization problem utilizing the collected reference human gait as reference is utilized to formally design stable multicontact 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 multicontact prosthetic walking captures the essentials of natural human walking both kinematically and kinetically.Note to Practitioners-Variable impedance control, as one of the most popular prosthetic controllers, has been used widely on powered prostheses with notable success. However, due to the passivity of this controller, heuristic feedback is required to adjust the control parameters for different subjects and motion modes. The end result is extensive testing time for users, coupled with non-optimal performance of prostheses. Motivated by the shortcomings in the current state-of-the-art, this work proposes a novel systematic methodology-including gait generation and optimization-based control based on a multidomain hybrid system-to achieve prosthetic walking for a given subject. aims to improve control optimality and efficiency while potentially reducing clinical tuning. The overarching technology utilized in this paper is the use of nominal human trajectories coupled with formal models and controllers that circumvent the need for excessive hand-tuning. In particular, rather than using a prerecorded trajectory (as is common), this work takes a different approach by using a human-inspired optimization problem to design a human-like gait for the amputee automatically. The proposed optimization framework uses the trajectory of a healthy subject as the reference and is subject to specific constraints (to ensure smooth transitions, torque and angle limitations) such that the output gait is applicable for implementation on the prosthetic device directly. The results of the offline optimization are then utilized to synthesize an online real-time optimization-based feedback controller that allows for pointwise optimal tracking on the prosthesis, thereby impr...

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“…Each phase begins at time t p 0 and ends at t p f . These phases consist of 1) P1 from foot strike to mid stance denoted by passing a threshold θ sf < thr [2], 2) P2 from mid stance to foot lift [25], 3) P3 from foot lift to full knee extension (i.e.θ nsk < 0), 4) P4 from full knee extension to foot strike [25].…”

Section: Fig 3: Separation Of Gait Into Four Phasesmentioning

confidence: 99%

Learning impedance controller parameters for lower-limb prostheses

Aghasadeghi

Zhao

Hargrove

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Impedance control is a common framework for control of lower-limb prosthetic devices. This approach requires choosing many impedance controller parameters. In this paper, we show how to learn these parameters for lower-limb prostheses by observation of unimpaired human walkers. We validate our approach in simulation of a transfemoral amputee, and we demonstrate the performance of the learned parameters in a preliminary experiment with a lower-limb prosthetic device.

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Outputs of human walking for bipedal robotic controller design

Cited by 18 publications

References 21 publications

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

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

Multicontact Locomotion on Transfemoral Prostheses via Hybrid System Models and Optimization-Based Control

Learning impedance controller parameters for lower-limb prostheses

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