Improved GelSight tactile sensor for measuring geometry and slip
Name
1708.00922.pdf
Description
Submitted version
Size
5.26 MB
Format
Adobe PDF
Checksum (MD5)
60aa3549a2889faca39e47e43a1ae5f8
Author(s)
Dong, Siyuan
Yuan, Wenzhen
Adelson, Edward H
Date Issued
December 2017
Journal
IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Dong, Siyuan et al. "Improved GelSight tactile sensor for measuring geometry and slip." IEEE/RSJ International Conference on Intelligent Robots and Systems, September 2017, Institute of Electrical and Electronics Engineers, December 2017. © 2017 IEEE
Version
Original manuscript
Abstract
A GelSight sensor uses an elastomeric slab covered with a reflective membrane to measure tactile signals. It measures the 3D geometry and contact force information with high spacial resolution, and successfully helped many challenging robot tasks. A previous sensor [1], based on a semi-specular membrane, produces high resolution but with limited geometry accuracy. In this paper, we describe a new design of GelSight for robot gripper, using a Lambertian membrane and new illumination system, which gives greatly improved geometric accuracy while retaining the compact size. We demonstrate its use in measuring surface normals and reconstructing height maps using photometric stereo. We also use it for the task of slip detection, using a combination of information about relative motions on the membrane surface and the shear distortions. Using a robotic arm and a set of 37 everyday objects with varied properties, we find that the sensor can detect translational and rotational slip in general cases, and can be used to improve the stability of the grasp.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/iros.2017.8202149
