Virtual Texture Generated Using Elastomeric Conductive Block Copolymer in a Wireless Multimodal Haptic Glove

Virtual Texture Generated Using Elastomeric Conductive Block Copolymer in a Wireless Multimodal Haptic Glove
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DOI:
10.1002/aisy.202000018
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发表时间:
2020-04-01
影响因子:
7.4
通讯作者:
Lipomi, Darren J.
Lipomi, Darren J.
中科院分区:
计算机科学3区
文献类型:
--
作者:
Keef, Colin, V;Kayser, Laure, V;Lipomi, Darren J.

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触觉装置通常更善于模仿材料的本体性质,而不是模仿表面性质。在此,描述了一种触觉手套,其能够产生使人联想到三种类型的近表面性质的感觉:硬度、温度和粗糙度。为了实现这种混合刺激模式,结合了三种类型的触觉致动器:振动触觉电机,热电设备和由实验室合成的可拉伸导电聚合物制成的电触觉电极。该聚合物由可拉伸的聚阴离子组成,其用作聚(3,4-乙撑二氧噻吩)聚合的支架。使用受控自由基聚合来合成支架,以提供相对于金属具有低分散性、相对高的导电性和低阻抗的材料。该手套配备了柔性传感器,可以在虚拟现实(VR)中控制机器人手和手。在心理物理学实验中,人类参与者能够辨别VR中的电触觉、振动触觉和热刺激的组合。接受过将这些感觉与粗糙度、硬度和温度联系起来的训练的参与者的总体准确率为98%,而未经训练的参与者的准确率为85%。类似地,可以使用配备有压力和温度传感器的机器人手来传达感觉。
Haptic devices are in general more adept at mimicking the bulk properties of materials than they are at mimicking the surface properties. Herein, a haptic glove is described which is capable of producing sensations reminiscent of three types of near-surface properties: hardness, temperature, and roughness. To accomplish this mixed mode of stimulation, three types of haptic actuators are combined: vibrotactile motors, thermoelectric devices, and electrotactile electrodes made from a stretchable conductive polymer synthesized in the laboratory. This polymer consists of a stretchable polyanion which serves as a scaffold for the polymerization of poly(3,4-ethylenedioxythiophene). The scaffold is synthesized using controlled radical polymerization to afford material of low dispersity, relatively high conductivity, and low impedance relative to metals. The glove is equipped with flex sensors to make it possible to control a robotic hand and a hand in virtual reality (VR). In psychophysical experiments, human participants are able to discern combinations of electrotactile, vibrotactile, and thermal stimulation in VR. Participants trained to associate these sensations with roughness, hardness, and temperature have an overall accuracy of 98%, whereas untrained participants have an accuracy of 85%. Sensations can similarly be conveyed using a robotic hand equipped with sensors for pressure and temperature.