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 language | English |
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Title of host publication | Proceedings - SIGGRAPH 2024 Conference Papers |
Editors | Stephen N. Spencer |
Publisher | Association for Computing Machinery, Inc |
ISBN (Electronic) | 9798400705250 |
DOIs | |
State | Published - 13 Jul 2024 |
Externally published | Yes |
Event | SIGGRAPH 2024 Conference Papers - Denver, United States Duration: 28 Jul 2024 → 1 Aug 2024 |
Publication series
Name | Proceedings - SIGGRAPH 2024 Conference Papers |
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Conference
Conference | SIGGRAPH 2024 Conference Papers |
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Country/Territory | United States |
City | Denver |
Period | 28/07/24 → 1/08/24 |
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