Design and Verification of Tactile Sensor for Texture Recognition

YAN Yan; XIE Wen-ao; ZAHNG Yuan-hang; ZHANG Chun

Chinese

您当前的位置：

首页 >

文章列表页 >

Design and Verification of Tactile Sensor for Texture Recognition

更新时间：2026-09-04

- Design and Verification of Tactile Sensor for Texture Recognition
- Vol. 34, Issue 12, Pages: 59-62(2017)
- 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：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
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

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Monte carlo analysis of V-layout trench SiC neutron detector

Research on the design of blockchain-based AI-generated content traceability framework

Research on assembly action recognition based on MSS-YOLO-MPHands fusion architecture

High gain stability high temperature operational amplifier based on reverse body bias

Design of ultra-low power real-time clock circuits

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰