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dc.contributor.authorDong, Siyuan
dc.contributor.authorYuan, Wenzhen
dc.contributor.authorAdelson, Edward H
dc.date.accessioned2020-08-17T18:57:36Z
dc.date.available2020-08-17T18:57:36Z
dc.date.issued2017-12
dc.date.submitted2017-09
dc.identifier.isbn9781538626825
dc.identifier.urihttps://hdl.handle.net/1721.1/126631
dc.description.abstractA 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.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/iros.2017.8202149en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleImproved GelSight tactile sensor for measuring geometry and slipen_US
dc.typeArticleen_US
dc.identifier.citationDong, 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 IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.relation.journalIEEE/RSJ International Conference on Intelligent Robots and Systemsen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-09-27T17:00:15Z
dspace.date.submission2019-09-27T17:00:20Z
mit.metadata.statusComplete


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