Sensing and Recognizing Surface Textures Using a GelSight Sensor
Name
Adelson_Sensing and Recognizing.pdf
Size
1.34 MB
Format
Adobe PDF
Checksum (MD5)
cacfd07397a8166241f9ff74926c6057
Author(s)
Li, Rui
Adelson, Edward H.
Date Issued
June 2013
Journal
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Li, Rui, and Edward H. Adelson. “Sensing and Recognizing Surface Textures Using a GelSight Sensor.” 2013 IEEE Conference on Computer Vision and Pattern Recognition (n.d.).
Version
Author's final manuscript
Abstract
Sensing surface textures by touch is a valuable capability for robots. Until recently it was difficult to build a compliant sensor with high sensitivity and high resolution. The GelSight sensor is compliant and offers sensitivity and resolution exceeding that of the human fingertips. This opens the possibility of measuring and recognizing highly detailed surface textures. The GelSight sensor, when pressed against a surface, delivers a height map. This can be treated as an image, and processed using the tools of visual texture analysis. We have devised a simple yet effective texture recognition system based on local binary patterns, and enhanced it by the use of a multi-scale pyramid and a Hellinger distance metric. We built a database with 40 classes of tactile textures using materials such as fabric, wood, and sandpaper. Our system can correctly categorize materials from this database with high accuracy. This suggests that the GelSight sensor can be useful for material recognition by robots.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CVPR.2013.164
