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Estimating the Deformability of Elastic Materials using Optical Flow and Position-based Dynamics
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Biotechnology (BIO), Protein Technology.ORCID iD: 0000-0002-9747-1399
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-3731-0582
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2314-2880
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-5750-9655
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2015 (English)In: Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on, IEEE conference proceedings, 2015, 965-971 p.Conference paper, Published paper (Refereed)
Abstract [en]

Knowledge of the physical properties of objects is essential in a wide range of robotic manipulation scenarios. A robot may not always be aware of such properties prior to interaction. If an object is incorrectly assumed to be rigid, it may exhibit unpredictable behavior when grasped. In this paper, we use vision based observation of the behavior of an object a robot is interacting with and use it as the basis for estimation of its elastic deformability. This is estimated in a local region around the interaction point using a physics simulator. We use optical flow to estimate the parameters of a position-based dynamics simulation using meshless shape matching (MSM). MSM has been widely used in computer graphics due to its computational efficiency, which is also important for closed-loop control in robotics. In a controlled experiment we demonstrate that our method can qualitatively estimate the physical properties of objects with different degrees of deformability.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 965-971 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-175162DOI: 10.1109/HUMANOIDS.2015.7363486ISI: 000377954900145Scopus ID: 2-s2.0-84962249847OAI: oai:DiVA.org:kth-175162DiVA: diva2:860060
Conference
IEEE-RAS International Conference on Humanoid Robots, November 3-5, KIST, Seoul, Korea
Note

QC 20160217

Available from: 2015-10-09 Created: 2015-10-09 Last updated: 2016-12-22Bibliographically approved

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Güler, RezanPauwels, KarlPieropan, AlessandroKjellström, HedvigKragic, Danica

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Computer Vision and Active Perception, CVAPCentre for Autonomous Systems, CASProtein Technology
Computer Vision and Robotics (Autonomous Systems)

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