Model-free vision-based shaping of deformable plastic materials

Andrea Cherubini, Valerio Ortenzi, Akansel Cosgun, Robert Lee, Peter Corke

Research output: Contribution to journalArticleResearchpeer-review

25 Citations (Scopus)


We address the problem of shaping deformable plastic materials using non-prehensile actions. Shaping plastic objects is challenging, because they are difficult to model and to track visually. We study this problem, by using kinetic sand, a plastic toy material that mimics the physical properties of wet sand. Inspired by a pilot study where humans shape kinetic sand, we define two types of actions: pushing the material from the sides and tapping from above. The chosen actions are executed with a robotic arm using image-based visual servoing. From the current and desired view of the material, we define states based on visual features such as the outer contour shape and the pixel luminosity values. These are mapped to actions, which are repeated iteratively to reduce the image error until convergence is reached. For pushing, we propose three methods for mapping the visual state to an action. These include heuristic methods and a neural network, trained from human actions. We show that it is possible to obtain simple shapes with the kinetic sand, without explicitly modeling the material. Our approach is limited in the types of shapes it can achieve. A richer set of action types and multi-step reasoning is needed to achieve more sophisticated shapes.

Original languageEnglish
Pages (from-to)1739-1759
Number of pages21
JournalInternational Journal of Robotics Research
Issue number14
Publication statusPublished - 25 Feb 2020


  • deformable plastic objects
  • Robotic manipulation
  • visual servoing

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