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Improved stability of haptic human-robot interfaces using measurement of human arm stiffness

机译:通过测量人体手臂刚度提高触觉人机界面的稳定性

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摘要

Necessary physical contact between an operator and a force feedback haptic device creates a coupled system consisting of human and machine. This contact, combined with the natural human tendency to increase arm stiffness to attempt to stabilize its motion, can reduce the stability of the system. This paper proposes a method to increase stability on demand while maintaining speed and performance. Operator arm stiffness is not directly measurable, so controllers cannot typically account for this issue. The causes of arm end-point stiffness are examined as related to system stability, and a method for estimating changes in arm stiffness based on arm muscle activity was designed to provide a robotic controller with additional information about the operator. This was accomplished using electromyograms (EMGs) to measure muscle activities and estimating the level of arm stiffness, which was used to adjust the dynamic characteristics of an impedance controller. To support this design, the correlation between EMGs and arm stiffness was validated experimentally. Further experiments characterized the effects of the designed system on operator performance. This showed increased stability and faster, more accurate movements using the compensating system. Such a system could be used in many applications, including force assisting devices in industrial facilities.
机译:操作员和力反馈触觉设备之间必要的物理接触创造了一个由人和机器组成的耦合系统。这种接触,加上人类增加手臂僵硬以试图稳定其运动的自然倾向,会降低系统的稳定性。本文提出了一种在保持速度和性能的同时提高按需稳定性的方法。操作员手臂的刚度无法直接测量,因此控制器通常无法解决此问题。研究了手臂终点刚度的原因与系统稳定性有关,并设计了一种基于手臂肌肉活动估计手臂刚度变化的方法,为机器人控制器提供有关操作员的额外信息。这是使用肌电图 (EMG) 来测量肌肉活动并估计手臂僵硬水平来实现的,用于调整阻抗控制器的动态特性。为了支持这一设计,通过实验验证了肌电图与手臂刚度之间的相关性。进一步的实验表征了所设计的系统对操作员性能的影响。这表明使用补偿系统提高了稳定性,运动更快、更准确。这种系统可用于许多应用,包括工业设施中的力辅助装置。

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