Deep-Learning-Assisted Triboelectric Whisker Sensor Array for Real-Time Motion Sensing of Unmanned Underwater Vehicle

IF 6.4 3区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Bo Liu, Bowen Dong, Hao Jin, Peng Zhu, Zhaoyang Mu, Yuanzheng Li, Jianhua Liu, Zhaochen Meng, Xinyue Zhou, Peng Xu, Minyi Xu
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Abstract

Aquatic animals can perceive their surrounding flow fields through highly evolved sensory systems. For instance, a seal whisker array understands the hydrodynamic field that allows seals to forage and navigate in dark environments. In this work, a deep learning-assisted underwater triboelectric whisker sensor array (TWSA) is designed for the 3D motion estimation and near-field perception of unmanned underwater vehicles. Each sensor comprises a high aspect ratio elliptical whisker shaft, four sensing units at the root of the elliptical whisker shaft, and a flexible corrugated joint simulating the skin on the cheek surface of aquatic animals. The TWSA effectively identifies flow velocity and direction in the 3D underwater environments and exhibits a rapid response time of 19 ms, a high sensitivity of 0.2V/ms−1, and a signal-to-noise ratio of 58 dB. The device also locks onto the frequency of the upstream wake vortex, achieving a minimal detection accuracy of 81.2%. Moreover, when integrated with an unmanned underwater vehicle, the TWSA can estimate 3D trajectories assisted by a trained deep learning model, with a root mean square error of ≈0.02. Thus, the TWSA-based assisted perception holds immense potential for enhancing unmanned underwater vehicle near-field perception and navigation capabilities across a wide range of applications.

Abstract Image

用于无人潜航器实时运动感应的深度学习辅助三电须传感器阵列
水生动物可以通过高度进化的感官系统感知周围的流场。例如,海豹胡须阵列能够理解水动力场,从而使海豹能够在黑暗环境中觅食和导航。在这项工作中,设计了一种深度学习辅助的水下三电须传感器阵列(TWSA),用于无人驾驶水下航行器的三维运动估计和近场感知。每个传感器由一个高纵横比椭圆晶须轴、位于椭圆晶须轴根部的四个传感单元和一个模拟水生动物颊面皮肤的柔性波纹接头组成。TWSA 能有效识别三维水下环境中的流速和流向,其响应时间为 19 毫秒,灵敏度高达 0.2V/ms-1,信噪比为 58 分贝。该装置还能锁定上游漩涡的频率,最低检测精度可达 81.2%。此外,当与无人驾驶水下航行器集成时,TWSA 可在训练有素的深度学习模型辅助下估计三维轨迹,均方根误差≈0.02。因此,基于 TWSA 的辅助感知技术在增强无人潜航器的近场感知和导航能力方面具有广泛应用的巨大潜力。
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来源期刊
Advanced Materials Technologies
Advanced Materials Technologies Materials Science-General Materials Science
CiteScore
10.20
自引率
4.40%
发文量
566
期刊介绍: Advanced Materials Technologies Advanced Materials Technologies is the new home for all technology-related materials applications research, with particular focus on advanced device design, fabrication and integration, as well as new technologies based on novel materials. It bridges the gap between fundamental laboratory research and industry.
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