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Origami structures enabled by folding and unfolding can create complex 3Dshapes. However, even a small 3D shape can have large 2D unfoldings. The hugeinitial dimension of the 2D flattened structure makes fabrication difficult,and defeats the main purpose, namely compactness, of many origami-inspiredengineering. In this work, we propose a novel algorithmic kirigami method thatprovides super compaction of an arbitrary 3D shape with non-negligible surfacethickness called "algorithmic stacking". Our approach computationally finds away of cutting the thick surface of the shape into a strip. This strip forms aHamiltonian cycle that covers the entire surface and can realize transformationbetween two target shapes: from a super compact stacked shape to the input 3Dshape. Depending on the surface thickness, the stacked structure takes merely0.001% to 6% of the original volume. This super compacted structure not onlycan be manufactured in a workspace that is significantly smaller than theprovided 3D shape, but also makes packing and transportation easier for adeployable application. We further demonstrate that, the proposed stackablestructure also provides high pluripotency and can transform into multiple 3Dtarget shapes if these 3D shapes can be dissected in specific ways and form acommon stacked structure. In contrast to many designs of origami structure thatusually target at a particular shape, our results provide a universal platformfor pluripotent 3D transformable structures.

Super Compaction and Pluripotent Shape Transformation via Algorithmic Stacking for 3D Deployable Structures