Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, 920-1192, Japan.
College of Science and Engineering, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, 920-1192, Japan.
Sci Rep. 2022 Jul 30;12(1):13096. doi: 10.1038/s41598-022-17026-0.
Skin-like soft sensors are key components for human-machine interfaces; however, the simultaneous sensing of several types of stimuli remains challenging because large-scale sensor integration is required with numerous wire connections. We propose an optical high-resolution multimodal sensing approach, which does not require integrating multiple sensors. This approach is based on the combination of an optical scattering phenomenon, which can encode the information of various stimuli as a speckle pattern, and a decoding technique using deep learning. We demonstrate the simultaneous sensing of three different physical quantities-contact force, contact location, and temperature-with a single soft material. Another unique capability of the proposed approach is spatially continuous sensing with an ultrahigh resolution of few tens of micrometers, in contrast to previous multimodal sensing approaches. Furthermore, a haptic soft device is presented for a human-machine interface. Our approach encourages the development of high-performance smart skin-like sensors.
皮肤般柔软的传感器是人机接口的关键组件;然而,由于需要通过大量的线连接来集成多个传感器,因此同时感知多种类型的刺激仍然具有挑战性。我们提出了一种光学高分辨率多模态传感方法,该方法不需要集成多个传感器。该方法基于光学散射现象的结合,该现象可以将各种刺激的信息编码为散斑图案,并且使用深度学习进行解码技术。我们展示了使用单个软材料同时感测三种不同的物理量-接触力,接触位置和温度。与先前的多模态传感方法相比,所提出的方法的另一个独特功能是具有数十微米的超高分辨率的空间连续感测。此外,还提出了用于人机接口的触觉软设备。我们的方法鼓励开发高性能智能皮肤状传感器。