COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami
This work addresses the challenge of generating physical art that satisfies both strict geometric constraints and subjective aesthetics, providing a tool for artists and designers in computational origami.
COrigami is an end-to-end AI pipeline that generates flat-foldable origami crease patterns from natural language descriptions, integrating geometric constraints with aesthetic evaluation. The system produces structurally valid starting points that human artists can refine, demonstrating reliable co-creativity in a mathematically rigorous domain.
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.