用声音变化测弯曲，柔性传感器精度超3.5米⁻¹
Soft Acoustic Curvature Sensor: Design and Development
- 通过声波在柔性通道中传播变化感知弯曲程度
- 实测曲率范围0~60米⁻¹，误差小于3.5米⁻¹
- 适合软体机器人、可穿戴设备等柔性场景
本文提出一种新型软性声学曲率（Soft Acoustic Curvature, SAC）传感器。该传感器将音频组件集成于柔性结构中，在内部设置声学通道。一端的扬声器发出参考声波，另一端麦克风接收信号。前期研究发现声波能量损耗随通道形变而变化，因此设计了可大幅弯曲的通道结构。采用机器学习模型建立形变与声信号调制间的复杂映射关系，对比多种频率和模型以提升曲率检测精度。传感器由柔性材料结合3D打印制成，实验验证显示其在0至60米⁻¹曲率范围内测量误差始终低于3.5米⁻¹。结果证明该方法在曲率估计中的有效性。凭借柔性结构，SAC传感器在软体机器人领域具有应用潜力，如连续体机械臂、软夹持器及可穿戴设备的形状感知。
原文摘要 · Abstract (English)
This paper introduces a novel Soft Acoustic Curvature (SAC) sensor. SAC incorporates integrated audio components and features an acoustic channel within a flexible structure. A reference acoustic wave, generated by a speaker at one end of the channel, propagates and is received by a microphone at the other channel's end. Our previous study revealed that acoustic wave energy dissipation varies with acoustic channel deformation, leading us to design a novel channel capable of large deformation due to bending. We then use Machine Learning (ML) models to establish a complex mapping between channel deformations and sound modulation. Various sound frequencies and ML models were evaluated to enhance curvature detection accuracy. The sensor, constructed using soft material and 3D printing, was validated experimentally, with curvature measurement errors remaining within 3.5 m-1 for a range of 0 to 60 m-1 curvatures. These results demonstrate the effectiveness of the proposed method for estimating curvatures. With its flexible structure, the SAC sensor holds potential for applications in soft robotics, including shape measurement for continuum manipulators, soft grippers, and wearable devices.
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