计算机科学
人工智能
工程类
特征(语言学)
计算机视觉
稳健性(进化)
控制工程
噪音(视频)
智能传感器
传感器融合
作者
Baijin Mao,Yedong Huang,Yuyaocen Xiang,Wenbo Liu,Xunlong Shi,Xiang Qian,Juntian Qu
出处
期刊:
日期:2026-04-02
卷期号:5 (1)
标识
DOI:10.1038/s44172-026-00653-0
摘要
Traditional multimodal flexible sensors struggle with system integration, limited node scalability, and overall robustness, posing multiple critical challenges. Inspired by the tiger-shark scalp, we present BDMFS, a robust bionic distributed multimodal flexible sensor, integrating an S-shaped optical network mimicking subcutaneous mechanoreceptors with a self-powered triboelectric interface emulating ampullae-based proximity sensing. A microstructured elastic dielectric layer serves as both optical substrate and triboelectric layer, providing exceptional flexibility, mechanical robustness, and environmental adaptability under diverse conditions. BDMFS enables spatiotemporally synchronized perception of proximity (~ 100 mm) and tactile (~ 5 ms) stimuli, detecting gentle touches of 0.25 g while withstanding 6.26 MPa pressures. Coupled with machine-learning, it achieves 95.26% object-proximity recognition accuracy, demonstrated in real-time virtual music teaching, adaptive grasping under low light, and wrist-mounted underwater teleoperation, highlighting its potential for intelligent control and advanced human-robot interaction in extreme environments. Traditional flexible sensors struggle with synchronized multimodal perception and robustness, limiting their performance in extreme environments. Baijin Mao and colleagues propose an ultra-robust bionic distributed multimodal flexible sensor inspired by tiger-shark skin.
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