English

Robotic Dough Shaping

Robotics 2022-10-06 v2 Artificial Intelligence Computer Vision and Pattern Recognition

Abstract

Robotic manipulation of deformable objects gains great attention due to its wide applications including medical surgery, home assistance, and automatic food preparation. The ability to deform soft objects remains a great challenge for robots due to difficulties in defining the problem mathematically. In this paper, we address the problem of shaping a piece of dough-like deformable material into a 2D target shape presented upfront. We use a 6 degree-of-freedom WidowX-250 Robot Arm equipped with a rolling pin and information collected from an RGB-D camera and a tactile sensor. We present and compare several control policies, including a dough shrinking action, in extensive experiments across three kinds of deformable materials and across three target dough shape sizes, achieving the intersection over union (IoU) of 0.90. Our results show that: i) rolling dough from the highest dough point is more efficient than from the 2D/3D dough centroid; ii) it might be better to stop the roll movement at the current dough boundary as opposed to the target shape outline; iii) the shrink action might be beneficial only if properly tuned with respect to the expand action; and iv) the Play-Doh material is easier to shape to a target shape as compared to Plasticine or Kinetic sand. Video demonstrations of our work are available at https://youtu.be/ZzLMxuITdt4

Keywords

Cite

@article{arxiv.2208.00386,
  title  = {Robotic Dough Shaping},
  author = {Jan Ondras and Di Ni and Xi Deng and Zeqi Gu and Henry Zheng and Tapomayukh Bhattacharjee},
  journal= {arXiv preprint arXiv:2208.00386},
  year   = {2022}
}

Comments

To be published in International Conference on Control, Automation and Systems (ICCAS), 2022

R2 v1 2026-06-25T01:21:31.062Z