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Learning to Measure the Static Friction Coefficient in Cloth Contact

Abdullah-Haroon Rasheed 1 Victor Romero 1 Florence Bertails-Descoubes 1 Stefanie Wuhrer 2 Jean-Sébastien Franco 2 Arnaud Lazarus 3
1 ELAN - ModELisation de l'apparence des phénomènes Non-linéaires
LJK - Laboratoire Jean Kuntzmann, Inria Grenoble - Rhône-Alpes
2 MORPHEO - Capture and Analysis of Shapes in Motion
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP [2020-....] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2020-....]
Abstract : Measuring friction coefficients between cloth and an external body is a longstanding issue in mechanical engineering, never yet addressed with a pure vision-based system. The latter offers the prospect of simpler, less invasive friction measurement protocols compared to traditional ones,and can vastly benefit from recent deep learning advances. Such a novel measurement strategy however proves challenging, as no large labelled dataset for cloth contact exists, and creating one would require thousands of physics work-bench measurements with broad coverage of cloth-material pairs. Using synthetic data instead is only possible assuming the availability of a soft-body mechanical simulator with true-to-life friction physics accuracy, yet to be verified. We propose a first vision-based measurement network forfriction between cloth and a substrate, using a simple and repeatable video acquisition protocol. We train our network on purely synthetic data generated by a state-of-the-art frictional contact simulator, which we carefully calibrate and validate against real experiments under controlled conditions. We show promising results on a large set of contact pairs between real cloth samples and various kinds of substrates, with 93.6% of all measurements predicted within 0.1 range of standard physics bench measurements.
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https://hal.inria.fr/hal-02511646
Contributor : Abdullah Haroon Rasheed <>
Submitted on : Monday, March 23, 2020 - 3:19:30 PM
Last modification on : Monday, October 12, 2020 - 11:16:02 AM

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  • HAL Id : hal-02511646, version 1

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Abdullah-Haroon Rasheed, Victor Romero, Florence Bertails-Descoubes, Stefanie Wuhrer, Jean-Sébastien Franco, et al.. Learning to Measure the Static Friction Coefficient in Cloth Contact. CVPR 2020 - IEEE Conference on Computer Vision and Pattern Recognition, Jun 2020, Seattle, United States. pp.1-10. ⟨hal-02511646⟩

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