纹理识别触觉传感器的设计与实现

闫岩; 谢文遨; 张远航; 张春

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纹理识别触觉传感器的设计与实现

更新时间：2026-09-04

- 纹理识别触觉传感器的设计与实现
- Design and Verification of Tactile Sensor for Texture Recognition
- 微电子学与计算机 2017年34卷第12期页码：59-62
- 作者机构：
  
  清华大学微电子学研究所,北京,100084
- 作者简介：
- 基金信息：
  
  国家自然科学基金 61327809
- DOI：
  中图分类号：
- 纸质出版：2017
- 稿件说明：
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闫岩, 谢文遨, 张远航, 张春. 纹理识别触觉传感器的设计与实现[J]. 微电子学与计算机, 2017, 34(12): 59-62.

YAN Yan, XIE Wen-ao, ZAHNG Yuan-hang, et al. Design and Verification of Tactile Sensor for Texture Recognition[J]. 2017, 34(12): 59-62.
闫岩, 谢文遨, 张远航, 张春. 纹理识别触觉传感器的设计与实现[J]. 微电子学与计算机, 2017, 34(12): 59-62. DOI：

YAN Yan, XIE Wen-ao, ZAHNG Yuan-hang, et al. Design and Verification of Tactile Sensor for Texture Recognition[J]. 2017, 34(12): 59-62. DOI：

摘要

为了解决机器人手指在抓取物体时无法识别其表面纹理信息的问题

设计了一种基于视觉的纹理识别触觉传感器.该传感器的硬件部分包括弹性体、照明装置和摄像头

而算法部分则是直接运用旋转不变LBP算法将拍摄到的纹理图像进行计算识别.为了加快传感器的速度并拓宽其适用范围

将算法移植到硬件电路并在FPGA上进行了验证.实验结果证明该传感器不仅可以识别包括指纹、皮革、织物、纸张等在内的12种纹理

而且可以达到24 f/s帧率的实时性处理.

Abstract

A vision-based tactile sensor is designed to satisfy the need of texture classification when the robotic hand grasping an object. The sensor includes three parts

which are a slab of elastomer

lighting devices and a camera. After obtaining clear images from this sensor

invariant LBP algorithm is used to determine which type the texture belongs to. In order to accelerate the computation speed and widen the use range

the algorithm is transplanted to circuits and verified in FPGA. Tests showed that the sensor can recognize 12 types of texture

including fingerprints

leather

fabric and so on. It can also get a real time result with the speed of 24fps.

关键词

Keywords

references

Johnson M K, Cole F. Microgeometry capture using elastometric sensor, graphics[J]. ACM transactions on, 2011, 30(4) : 46. DOI: 46

Rui Li, Edward H Adelson. Sensng and recognizing surface textures using a gelsight sensor[C]// Computer Vision and Pattern Recognition, IEEE Conference. IEEE, 2013: 1241-1247.

Fishel J A, Loeb G E. Sensing tactile microvibrations with the Biotac[C]// The Fourth IEEE RAS/EMBS International Conference on Biomedical Robotics and Bio mechatronics. IEEE, 2012.

Timo Ojala, Matti Pietikainen. Multiresolution gray-scale and rotation invariant texture classification with local binary pattern[J]. Pattern Analusis and Machine Intelligence, ACM transactions on, 2000, 24 (7) : 404-420. DOI: 404

Jiang Hanjun, Zhu Xiyang. Vision-based tactile sensor using depth from defocus for artificial finger in hand prosthesis[J]. Electronics Letters, 2016, 52 (20) : 1665-1667. DOI: 1665

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