Generalized Virtual Fixtures for Shared-Control Grasping in Brain-Machine Interfaces.
Generalized Virtual Fixtures for Shared-Control Grasping in Brain-Machine Interfaces.
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DOI：
10.1109/iros.2013.6696371
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发表时间：
2013-11
期刊：
影响因子：
--
通讯作者：
Velliste M
中科院分区：
文献类型：
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作者：
Clanton ST;Rasmussen RG;Zohny Z;Velliste M
在脑机接口（BMI）假肢系统中，大脑活动的记录被用来控制外部设备，如计算机或机器人。BMI系统显示出最高的控制保真度，它使用直接从大脑中的微电极记录的神经信号来控制上肢假肢。这些已经从允许控制计算机屏幕上光标的二维和三维移动[1]，[2]发展到控制前四个[3]，[4]和最近的七个自由度（DoF）（图1）[5]，[6]。这些类型的系统需要训练用户同时控制大量DoF的方法。本文提出了一种新的共享控制制导方法。这种“正跨度”虚拟夹具的方法扩展了虚拟夹具的概念，以引导脑控机器人手的平移和旋转自由度朝向允许物体被抓握的机器人姿势的整组。该系统用于成功训练猴子操作7-DoF BMI [5]，直接导致用于在类似实验中指导人类受试者BMI控制的简化“正交阻抗”系统[6]。
In brain-machine interface (BMI) prosthetic systems, recordings of brain activity are used to control external devices such as computers or robots. BMI systems that have shown the highest fidelity of control use neural signals recorded directly from microelectrodes in the brain to control upper-limb prostheses. These have progressed from allowing control of 2 and 3 dimensional movement of a cursor on a computer screen [1], [2] to control of robot arms in first four [3], [4] and more recently seven degrees-of-freedom (DoF) (Fig. 1) [5], [6]. These types of systems require methods to train users to control large numbers of DoF simultaneously. In this paper we present a new method for shared-control guidance. This method of "Positive-Span" Virtual Fixturing extends the concept of Virtual Fixtures to guide both translational and rotational DoF of a brain-controlled robot hand toward whole sets of robot poses that would allow an object to be grasped. This system was used to successfully train monkeys to operate the 7-DoF BMI [5], leading directly to the simplified system of "ortho-impedance" used to guide human subject BMI control in a similar experiment [6].