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Robotic Fabric Flattening with Wrinkle Direction Detection

arXiv 2303.04909 ↗First posted 8 Mar 2023cs.RO cs.CVcited by 0

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Abstract (arXiv)

Deformable Object Manipulation (DOM) is an important field of research as it contributes to practical tasks such as automatic cloth handling, cable routing, surgical operation, etc. Perception is considered one of the major challenges in DOM due to the complex dynamics and high degree of freedom of deformable objects. In this paper, we develop a novel image-processing algorithm based on Gabor filters to extract useful features from cloth, and based on this, devise a strategy for cloth flattening tasks. We also evaluate the overall framework experimentally and compare it with three human operators. The results show that our algorithm can determine the direction of wrinkles on the cloth accurately in simulation as well as in real robot experiments. Furthermore, our dewrinkling strategy compares favorably to baseline methods. The experiment video is available on https://sites.google.com/view/robotic-fabric-flattening/home

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 41 references that are in the map. First posted on arXiv 8 Mar 2023.

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14 of 41 references.

References · 14

  1. 2018Sim-to-Real Reinforcement Learning for Deformable Object Manipulationcited by 124
  2. 2020SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulationcited by 118
  3. 2019End-to-End Robotic Reinforcement Learning without Reward Engineeringcited by 115
  4. 2019Learning to Manipulate Deformable Objects without Demonstrationscited by 76
  5. 2020Learning Predictive Representations for Deformable Objects Using Contrastive Estimationcited by 72
  6. 2021Dynamic Movement Primitives in Robotics: A Tutorial Surveycited by 45
  7. 2021Challenges and Outlook in Robotic Manipulation of Deformable Objectscited by 43
  8. 2020VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulationcited by 40
  9. 2019Dynamic Cloth Manipulation with Deep Reinforcement Learningcited by 26
  10. 2022Learning Deformable Object Manipulation from Expert Demonstrationscited by 18
  11. 2021Learning Latent Graph Dynamics for Visual Manipulation of Deformable Objectscited by 17
  12. 2021ILoSA: Interactive Learning of Stiffness and Attractorscited by 11
2 more
  1. 2018Cloth Manipulation Using Random-Forest-Based Imitation Learningcited by 7
  2. 2017Manipulating Highly Deformable Materials Using a Visual Feedback Dictionarycited by 5

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