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CNN-based Visual Servoing for Simultaneous Positioning and Flattening of Soft Fabric Parts
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  • Fuyuki Tokuda ,
  • Akira Seino ,
  • Akinari Kobayashi ,
  • Kazuhiro Kosuge ,
  • Fuyuki Tokuda
Fuyuki Tokuda
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Akira Seino
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Akinari Kobayashi
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Kazuhiro Kosuge
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Fuyuki Tokuda
Centre for Transformative Garment Production

Corresponding Author:[email protected]

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Abstract

This paper proposes CNN-based visual servoing for simultaneous positioning and flattening of a soft fabric part placed on a table by a dual manipulator system. We propose a network for multimodal data processing of grayscale images captured by a camera and force/torque applied to force sensors. The training dataset is collected by moving the real manipulators, which enables the network to map the captured images and force/torque to the manipulator’s motion in Cartesian space. We apply structured lighting to emphasize the features of the surface of the fabric part since the surface shape of the non-textured fabric part is difficult to recognize by a single grayscale image. Through experiments, we show that the fabric part with unseen wrinkles can be positioned and flattened by the proposed visual servoing scheme.
*The complete version of this preprint paper is in proceedings of ICRA 2023. Please refer to “https://ieeexplore.ieee.org/document/10160635”.