Speckle-based high-resolution multimodal soft sensing
Sho Shimadera, Kei Kitagawa, Koyo Sagehashi, Yoji Miyajima, Tomoaki Niiyama, Satoshi Sunada
Abstract
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.