| Literature DB >> 34138239 |
Ken Qin1, Chen Chen1, Xianjie Pu2, Qian Tang3, Wencong He1, Yike Liu1, Qixuan Zeng1, Guanlin Liu4, Hengyu Guo1, Chenguo Hu5.
Abstract
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.Entities:
Keywords: Gesture; Human-machine interaction; Magnetic array; Real-time; Sliding triboelectric sensor
Year: 2021 PMID: 34138239 PMCID: PMC8187499 DOI: 10.1007/s40820-020-00575-2
Source DB: PubMed Journal: Nanomicro Lett ISSN: 2150-5551
Fig. 1Structure of the Ma-s-TS. a Schematic diagram and multilayer structure of the Ma-s-TS. The insets: developing photograph of the magnetic array on the substrate and slider. b Overall structure diagram. c Magnetic array assisted contact-separation state (top and bottom). d Photograph of an as-fabricated sensor (scale bar: 1 cm)
Fig. 2Operating-principle of the Ma-s-TS. a Schematics of electron transfer process in the sliding. b Schematics of output signal in sliding process. c COSMOL simulation of potential distribution under various states in sliding process. d–f Test output signal corresponding to Fig. 2b
Fig. 3Characterization of the basic performance of Ma-s-TS. a–c Pulses produced from a Ma-s-TS when rotate through different angles (54°, 72°, and 90°) at rotation speed of 0.375 rps. d–f The pulses generated from a Ma-s-TS when rotate through 90° at different rotation speed (0.375, 0.50, and 0.625 rps)
Fig. 4Matching of two coupled parts of the slider. a Area adjustment diagram of the two parts. b Speed response range under different area ratio of part B to part A. c Test signals at rotation speed from 0.25 to 1.75 rps under area ratio of 0.8. d–f Enlarged signal of Fig. 4c at rotation speed of 0.25, 1.00, and 1.75 rps
Fig. 5Real-time gesture interaction demonstration. a Ma-s-TS worn on the fingers. b Positive and negative pulses represent straightening and bending of finger. c Real-time gesture interaction of robotic hand and human hand based on the signal of Fig. 5b. d–e Comparison with jmTQS [15] on cross talk between channels (d jmTQS, e Ma-s-TS)