【24h】

An improved human-robot interface by measurement of muscle stiffness

机译:通过测量肌肉僵硬度来改善人机界面

获取原文
获取原文并翻译 | 示例

摘要

Human contact with haptic devices introduces instabilities due to human operators' attemps to stiffen their arm to stabilize the system. Controllers often cannot measure arm stiffness and do not typically account for this. A method to effectively adjust the controller of a robotic force assist device to compensate for changes in operator arm stiffness was established. It was expected to achieve reduced oscillations and increased performance than one with fixed gains. The results could be used to design human-robot interfaces for force assisting devices. The compensating system used EMG signals to measure muscle activity, then estimated the stiffness of the human's arm. This was used to adjust the parameters of a haptic device's impedance controller based on a threshold. The system was then implemented on a small haptic device to study the effects with a human subjects. EMG signals were experimentally validated as an effective prediction of the stiffness of an operator's arm. The system was assessed in terms of performance and was found to provide improved stability and demonstrated the potential for increased performance.
机译:人体与触觉设备的接触会导致不稳定,这是由于人类操作员会试图加强手臂以稳定系统。控制器通常无法测量手​​臂的刚度,因此通常不会考虑这一点。建立了一种有效地调节机器人力辅助设备的控制器以补偿操作员手臂刚度变化的方法。与具有固定增益的振荡器相比,它有望减少振荡并提高性能。该结果可用于设计力辅助设备的人机界面。补偿系统使用EMG信号测量肌肉活动,然后估算人手臂的僵硬度。这用于基于阈值来调整触觉设备的阻抗控制器的参数。然后将该系统安装在小型触觉设备上,以研究人类受试者的影响。 EMG信号经过实验验证,可以有效预测操作员手臂的僵硬程度。对系统进行了性能评估,发现该系统提供了更高的稳定性,并展示了提高性能的潜力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号