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基于固液复合柔性触觉传感器阵列的精细纹理检测

Fine Texture Detection Based on a Solid-Liquid Composite Flexible Tactile Sensor Array.

作者信息

Liu Weiting, Zhang Guoshi, Zhan Binpeng, Hu Liang, Liu Tao

机构信息

State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310007, China.

出版信息

Micromachines (Basel). 2022 Mar 14;13(3):440. doi: 10.3390/mi13030440.

Abstract

Surface texture information plays an important role in the cognition and manipulation of an object. Vision and touch are the two main methods for extracting an object's surface texture information. However, vision is often limited since the viewing angle is uncertain during manipulation. In this article, we propose a fine surface texture detection method based on a stochastic resonance algorithm through a novel solid-liquid composite flexible tactile sensor array. A thin flexible layer and solid-liquid composite conduction structure on the sensor effectively reduce the attenuation of the contact force and enhance the sensitivity of the sensor. A series of ridge texture samples with different heights (0.9, 4, 10 μm), different widths (0.3, 0.5, 0.7, 1 mm), but the same spatial period (2 mm) of ridges were used in the experiment. The experimental results prove that the stochastic resonance algorithm can significantly improve the signal characteristic of the output signal of the sensor. The sensor has the capability to detect fine ridge texture information. The mean relative error of the estimation for the spatial period was 1.085%, and the ridge width and ridge height, respectively, have a monotonic mapping relationship with the corresponding model output parameters. The sensing capability to sense a fine texture of tactile senor surpasses the limit of human fingers.

摘要

表面纹理信息在物体的认知和操作中起着重要作用。视觉和触觉是提取物体表面纹理信息的两种主要方式。然而,视觉往往受到限制,因为在操作过程中视角不确定。在本文中,我们通过一种新型的固液复合柔性触觉传感器阵列,提出了一种基于随机共振算法的精细表面纹理检测方法。传感器上的薄柔性层和固液复合传导结构有效地降低了接触力的衰减,并提高了传感器的灵敏度。实验中使用了一系列具有不同高度(0.9、4、10μm)、不同宽度(0.3、0.5、0.7、1mm)但相同脊空间周期(2mm)的脊纹理样本。实验结果证明,随机共振算法能够显著改善传感器输出信号的信号特征。该传感器具有检测精细脊纹理信息的能力。空间周期估计的平均相对误差为1.085%,并且脊宽度和脊高度分别与相应的模型输出参数具有单调映射关系。触觉传感器感知精细纹理的传感能力超过了人类手指的极限。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e19e/8951775/fba9d9fd4d54/micromachines-13-00440-g001.jpg

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