Modal Folding: Discovering Smooth Folding Patterns for Sheet Materials using Strain-Space Modes

Pengbin Tang, Ronan Hinchet, Roi Poranne, Bernhard Thomaszewski, Stelian Coros

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Folding can transform mundane objects such as napkins into stunning works of art. However, finding new folding transformations for sheet materials is a challenging problem that requires expertise and real-world experimentation. In this paper, we present Modal Folding - an automated approach for discovering energetically optimal folding transformations, i.e., large deformations that require little mechanical work. For small deformations, minimizing internal energy for fixed displacement magnitudes leads to the well-known elastic eigenmodes. While linear modes provide promising directions for bending, they cannot capture the rotational motion required for folding. To overcome this limitation, we introduce strain-space modes - nonlinear analogues of elastic eigenmodes that operate on per-element curvatures instead of vertices. Using strain-space modes to determine target curvatures for bending elements, we can generate complex nonlinear folding motions by simply minimizing the sheet's internal energy. Our modal folding approach offers a systematic and automated way to create complex designs. We demonstrate the effectiveness of our method with simulation results for a range of shapes and materials, and validate our designs with physical prototypes.

Original languageEnglish
Title of host publicationProceedings - SIGGRAPH 2024 Conference Papers
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9798400705250
DOIs
StatePublished - 13 Jul 2024
Externally publishedYes
EventSIGGRAPH 2024 Conference Papers - Denver, United States
Duration: 28 Jul 20241 Aug 2024

Publication series

NameProceedings - SIGGRAPH 2024 Conference Papers

Conference

ConferenceSIGGRAPH 2024 Conference Papers
Country/TerritoryUnited States
CityDenver
Period28/07/241/08/24

Bibliographical note

Publisher Copyright:
© 2024 ACM.

Keywords

  • Computational Design
  • Folding
  • Nonlinear Modal Analysis
  • Origami

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Visual Arts and Performing Arts
  • Computer Graphics and Computer-Aided Design

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