Qin Ken, Chen Chen, Pu Xianjie, Tang Qian, He Wencong, Liu Yike, Zeng Qixuan, Liu Guanlin, Guo Hengyu, Hu Chenguo
Department of Applied Physics, State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, Chongqing University, Chongqing, 400044, People's Republic of China.
Center On Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, Guangxi, 530004, People's Republic of China.
Nanomicro Lett. 2021 Jan 5;13(1):51. doi: 10.1007/s40820-020-00575-2.
In human-machine interaction, robotic hands are useful in many scenarios. To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction. Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. With a finger's traction movement of flexion or extension, the sensor can induce positive/negative pulse signals. Through counting the pulses in unit time, the degree, speed, and direction of finger motion can be judged in real-time. The magnetic array plays an important role in generating the quantifiable pulses. The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway, respectively, thus improve the durability, low speed signal amplitude, and stability of the system. This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural, intuitive, and real-time human-robotic interaction.
在人机交互中,机器人手在许多场景中都很有用。通过手势而非手柄来操作机器人手将极大地提高人机交互的便利性和直观性。在此,我们展示了一种磁阵列辅助滑动摩擦电传感器,用于实现人手与机器人手之间的实时手势交互。随着手指进行屈伸的牵引运动,该传感器能够感应出正/负脉冲信号。通过计算单位时间内的脉冲数,可以实时判断手指运动的程度、速度和方向。磁阵列在产生可量化脉冲方面起着重要作用。所设计的两部分磁阵列可分别将滑动运动转化为接触-分离并限制滑动路径,从而提高系统的耐用性、低速信号幅度和稳定性。这种直接量化方法以及可穿戴手势传感器的优化为实现自然、直观和实时的人机交互提供了一种新策略。