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Assistance using adaptive oscillators: Robustness to errors in the identification of the limb parameters

机译:使用自适应振荡器的协助:肢体参数识别错误的稳健性

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This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.
机译:本文提供了对我们最近开发的使用自适应振荡器进行有节奏运动辅助的方法的鲁棒性分析。自适应振荡器是一种数学工具,能够提取准正弦测量运动的高级特征(即,振幅,频率,偏移),在这种情况下,是肘部的节律性屈伸。通过使用简单的逆动力学模型,系统可以预测人类参与者产生的扭矩,从而使估算扭矩的一部分通过一系列弹性致动器反馈,以提供运动辅助。本文的目标是双重的。首先,我们介绍了在我们的实验室中开发的新型1 DOF辅助设备。其次,我们推导基于模型的预测并进行实验验证,以测量运动频率随逆动力学模型的开放参数而变化的情况。因此,由于模型近似,本文提供了我们方法的鲁棒性估计。作为主要结果,本文揭示了运动频率对于阻尼系数估计中的误差特别有鲁棒性。这对于我们方法的适用性引起了极大的兴趣,该参数通常是最难识别的。

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