COrigami:一個共同設計可扁平摺疊且視覺可辨識摺紙的AI管線
COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami
June 24, 2026
作者: 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
cs.AI
摘要
儘管生成式AI在解決具有可驗證解法的問題上已取得顯著成功,但生成同時滿足嚴格幾何約束與主觀視覺美學的實體藝術作品仍是一項挑戰。本文提出一種方法,在計算摺紙這個數學上嚴謹的領域中應對這些難題——該領域將藝術設計置於平面可摺疊性方程式的框架內。我們介紹COrigami,一種端到端的AI驅動流程,透過從自然語言生成折痕圖案來輔助設計循環。此流程包含:生成語義骨架圖、計算基礎佈局、求解平面可摺疊的折痕圖案、塑形平面摺疊後的折痕圖案,以及透過基於自主美學評估循環的強化學習來優化生成模型。我們的系統扮演高度有效的協作助手,提供結構化的起點,讓人類藝術家能進一步擴展與雕塑。透過將演算法優化與自主美學評判相結合,本研究展示了AI系統如何滿足多目標物理約束,從而實現可靠且植基於數學的協同創造力。
English
While generative AI has achieved remarkable success in solving problems with verifiable solutions, generating physical art that satisfies both strict geometric constraints and subjective visual aesthetics remains a challenge. This paper presents an approach to tackle these difficulties in the domain of computational origami, a mathematically rigid environment that grounds artistic design within the equations of flat foldability. We present COrigami, an end-to-end AI-driven pipeline that assists the design cycle by generating crease patterns from natural language. Our 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 driven by an autonomous aesthetic evaluation loop. Our system acts as a highly effective collaborative assistant, generating structural starting points that human artists can further expand and shape. By integrating algorithmic optimisation with autonomous aesthetic critique, this work demonstrates how AI systems can satisfy multi-objective physical constraints to enable reliable, mathematically grounded co-creativity.