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Myoelectric teleoperation of a complex robotic hand

机译:复杂机械手的肌电遥操作

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Teleoperation continues to be a primary control mode in robotics applications, particularly for robots with complex hands. This paper details a novel method of teleoperation of complex anthropomorphic robotic hands: converting the myoelectric signal (generated by the operator's muscles during movement) into robot commands replicating the motion. Myoelectric prosthetic hands have used this user interface for over two decades; however, the feasibility of using this approach for commanding more than one degree-of-freedom, as in the pincher type grip in current myoelectric hands, has been in question. The research described in this paper addresses myoelectric control of NASA/Johnson Space Center's sixteen degree-of-freedom Utah/MIT Dextrous Hand for two grasping (key and chuck) options and three thumb motions (abduction, extension, and flexion). We discuss myoelectric signal processing approaches, data collection apparatus, and a realtime teleoperation implementation. We also present results in realtime discrimination of key and chuck grasps and offline discrimination of thumb motions. Our results include a 90% correct grasp selection rate and an 87% correct thumb motion selection, both using the myoelectric spectrum.
机译:遥操作仍然是机器人应用程序中的主要控制模式,尤其是对于复杂双手的机器人。本文详细介绍了一种复杂的拟人化机器人手遥操作的新方法:将肌电信号(由操作员的肌肉在运动过程中产生)转换为复制运动的机器人命令。肌电假肢已经使用了该用户界面超过二十年了。然而,使用这种方法来控制一个以上的自由度的可行性,例如在当前的肌电手的钳式握持中,一直受到质疑。本文描述的研究针对NASA / Johnson航天中心的16个自由度犹他州/ MIT陀螺手的肌电控制,用于两个抓握(键和卡盘)选项和三个拇指运动(外展,伸展和屈曲)。我们讨论了肌电信号处理方法,数据收集设备和实时遥操作实现。我们还提出了实时识别按键和卡盘抓握以及离线识别拇指动作的结果。我们的结果包括90%的正确抓握选择率和87%的正确拇指动作选择,均使用了肌电频谱。

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