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dc.contributor.authorWang, Shaoxiong
dc.contributor.authorWu, Jiajun
dc.contributor.authorSun, Xingyuan
dc.contributor.authorYuan, Wenzhen
dc.contributor.authorFreeman, William T.
dc.contributor.authorTenenbaum, Joshua B.
dc.contributor.authorAdelson, Edward H.
dc.date.accessioned2020-04-07T19:38:06Z
dc.date.available2020-04-07T19:38:06Z
dc.date.issued2018-10
dc.identifier.urihttps://hdl.handle.net/1721.1/124514
dc.description.abstractPerceiving accurate 3D object shape is important for robots to interact with the physical world. Current research along this direction has been primarily relying on visual observations. Vision, however useful, has inherent limitations due to occlusions and the 2D-3D ambiguities, especially for perception with a monocular camera. In contrast, touch gets precise local shape information, though its efficiency for reconstructing the entire shape could be low. In this paper, we propose a novel paradigm that efficiently perceives accurate 3D object shape by incorporating visual and tactile observations, as well as prior knowledge of common object shapes learned from large-scale shape repositories. We use vision first, applying neural networks with learned shape priors to predict an object's 3D shape from a single-view color image. We then use tactile sensing to refine the shape; the robot actively touches the object regions where the visual prediction has high uncertainty. Our method efficiently builds the 3D shape of common objects from a color image and a small number of tactile explorations (around 10). Our setup is easy to apply and has potentials to help robots better perform grasping or manipulation tasks on real-world objects. ©2018en_US
dc.description.sponsorshipONR MURI (no. N00014-16-1-2007)en_US
dc.language.isoen
dc.relation.isversionof10.1109/IROS.2018.8593430en_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.title3D shape perception from monocular vision, touch, and shape priorsen_US
dc.typeArticleen_US
dc.identifier.citationS. Wang et al., "3D shape perception from monocular vision, touch, and shape priors." Digest, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018 (Piscataway, N.J.: IEEE, 2018): p. 1606-13 doi 10.1109/IROS.2018.8593430 ©2018 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-05-28T15:30:52Z
dspace.date.submission2019-05-28T15:30:53Z


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