Soft Sensor / ソフトセンサ (2020-)

Overview

Soft sensors made of deformable materials, that are capable of sensing touches or gestures, have attracted considerable attention for use in tangible interfaces or soft robotics. However, to achieve multimodal gesture detection with soft sensors, prior studies have combined multiple sensors or utilized complex configurations with multiple wires. To achieve multimodal gesture sensing with a simpler configuration, a novel soft sensor consisting of a conductive foam with a single wire, was proposed in this study. This sensor was named as foamin and utilizes an impedance measurement technique at multiple frequencies called swept-frequency capacitive sensing (SFCS). Additionally, a surface-shielding method was designed for improving the detection performance of the sensor. Several patterns of foamin were implemented to investigate the detection accuracy and three application scenarios based on the sensor were proposed.

タッチやジェスチャ入力を感知でき、かつ柔らかい素材で構成されるソフトセンサは、タンジブルインターフェースやソフトロボティクスへの応用が注目されています。しかし、ソフトセンサーによるマルチモーダルなジェスチャ検知を実現するためには、複数のセンサを組み合わせたり、複数の配線を用いた複雑な構成を採る必要があるのが現状です。本研究では，よりシンプルな構成でマルチモーダルなジェスチャ検出を実現するために，導電性のスポンジと1本のワイヤで構成された新しいソフトセンサfoaminを提案します。このセンサはSFCSと呼ばれる複数の周波数でのインピーダンス測定技術を利用し、その変形やタッチの種類を識別します。さらにこのセンサの検出性能を向上させるために、表面のシールドのデザインを施しました。さらに本研究では、foaminを用いた3つのアプリケーションシナリオを提案しています。

本研究は、東京大学筧康明研究室とメルカリR4Dの共同研究による成果です。

Publication

[1] Rei Sakura, Changyo Han, Keisuke Watanabe, Ryosuke Yamamura, and Yasuaki Kakehi. 2022. Design of 3D-Printed Soft Sensors for Wire Management and Customized Softness. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI EA '22). Association for Computing Machinery, New York, NY, USA, Article 192, 1–5. https://doi.org/10.1145/3491101.3519906

[2] K. Watanabe, R. Yamamura, and Y. Kakehi, “foamin: A Deformable Sensor for Multi-Modal Inputs Based on Conductive Foam with a Single Wire” Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA’21), May, 2021, Yokohama, Japan, May 2021. https://doi.org/10.1145/3411763.3451547

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Patent

Patent pending.

Collaborator

xlab (The University of Tokyo)

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