AI可生成可折叠且视觉可识别的折纸设计，实现艺术与数学约束的协同创作。
COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami
- 通过自然语言生成折痕图，融合语义骨架与可折叠算法。
- 基于强化学习实现自动美学评估，提升视觉识别度。
- 适合艺术设计与工程折纸领域的跨学科协作应用。
尽管生成式AI在具有可验证解的问题上取得显著进展，但生成同时满足严格几何约束和主观视觉美感的实体艺术仍具挑战。本文针对计算折纸这一数学严谨的领域，提出COrigami——一个端到端的AI驱动管道，支持从自然语言生成折痕图案的设计流程。该流程包括生成语义骨架、计算基础排布、求解可平折折痕图、调整折痕形态，并利用由自主美学评估驱动的强化学习进行模型优化。系统作为高效协作助手，为人类艺术家提供可扩展的结构起点。通过整合算法优化与自主美学批判，本研究展示了如何在多目标物理约束下实现可靠、数学基础牢固的共创意创造。
原文摘要 · Abstract (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.
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