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Research on robot sewing method based on process modeling

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Abstract

At present, most clothing sewing relies on manual labor, and robot sewing has become a trend. However, different clothing styles have various sewing requirements. This poses a challenge for robot sewing, and the key to solving this challenge lies in the planning of robot operation trajectories. Although the shapes of sewing components are diverse, we can decompose them into the most basic straight lines and curved edges. In order to solve the trajectory planning problem in robot sewing process, this paper divides the sewing task into two parts: straight line and curve, and proposes a new robot sewing method based on task process decomposition. Firstly, The robot complex sewing task is divided into two parts: straight line and curve. Based on the extensibility, the sewing tension is predicted, and the robot linear sewing based on impedance control is realized. At the same time, the trajectory planning is carried out on the basis of the line identification of the curved edge to realize the curve sewing. Finally, the robot complex stitch sewing under different curvatures is realized on the built physical experiment platform. It is verified that the effectiveness of the robot sewing method based on process modeling.

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The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Author notes

  1. Fengming Li, Dang Hou, Tianyu Fu, Jiexin Song, Wenbin He and Rui Song contributed equally to this work.

Authors and Affiliations

  1. School of Information and Engineering, Shandong Jianzhu University, Jinan, 250101, Shandong, China

    Fengming Li

  2. School of Control Science and Engineering, Shandong University, Jinan, 250061, Shandong, China

    Fengming Li, Dang Hou, Tianyu Fu, Jiexin Song, Wenbin He & Rui Song

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  1. Fengming Li
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  2. Dang Hou
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  3. Tianyu Fu
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  4. Jiexin Song
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  5. Wenbin He
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Correspondence to Tianyu Fu or Rui Song.

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Li, F., Hou, D., Fu, T. et al. Research on robot sewing method based on process modeling. Int J Intell Robot Appl (2024). https://doi.org/10.1007/s41315-024-00326-1

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