COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami
Researchers have developed COrigami, an AI pipeline for co-designing flat-foldable visually recognizable origami. The pipeline generates crease patterns from natural language and involves multiple steps, including generating a semantic stick figure and refining the generated model using reinforcement learning. This work demonstrates how AI systems can satisfy multi-objective physical constraints to enable reliable, mathematically grounded co-creativity.
- ▪COrigami is an end-to-end AI-driven pipeline that assists the design cycle by generating crease patterns from natural language.
- ▪The pipeline involves generating a semantic stick figure, computing a base packing, solving for a flat-foldable crease pattern, shaping the flat-folded crease pattern, and refining the generated model using reinforcement learning.
- ▪The system acts as a highly effective collaborative assistant, generating structural starting points that human artists can further expand and shape.
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Computer Science > Artificial Intelligence arXiv:2606.26299 (cs) [Submitted on 24 Jun 2026] Title:COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami Authors:Tom Zahavy, Shaobo Hou, Thomas Tumiel, James Doran, Francesco Faccio, Xidong Feng, Alex Havrilla, Igor Khytryi, Chenglei Li, Lisa Schut, Vivek Veeriah, Arijan Abrashi, Michał Kosmulski, Robert J. Lang, Nick Robinson, Brandon Wong, Marcus Chiam, Gloria Fang, Satinder Singh View a PDF of the paper titled COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami, by Tom Zahavy and 17 other authors View PDF HTML (experimental) Abstract:While generative AI has achieved remarkable success in solving problems with verifiable solutions, generating physical art that satisfies both…
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