Convex partitions of polyhedra: a lower bound and worst-case optimal algorithm
SIAM Journal on Computing
Communications of the ACM - Robots: intelligence, versatility, adaptivity
The optimality of a certain purely recursive dissection for a sequentially n-divisible square
Computational Geometry: Theory and Applications - Special issue on Discrete and computational geometry
Dudeney Dissection of Polygons
JCDCG '98 Revised Papers from the Japanese Conference on Discrete and Computational Geometry
Hinged dissection of polyominoes and polyforms
Computational Geometry: Theory and Applications - Special issue: The 11th Candian conference on computational geometry - CCCG 99
Acute Triangulations of Polygons
Discrete & Computational Geometry
Locked and unlocked chains of planar shapes
Proceedings of the twenty-second annual symposium on Computational geometry
Hinged dissection of polypolyhedra
WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
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We prove that any finite collection of polygons of equal area has a common hinged dissection, that is, a chain of polygons hinged at vertices that can be folded in the plane continuously without self-intersection to form any polygon in the collection. This result settles the open problem about the existence of hinged dissections between pairs of polygons that goes back implicitly to 1864 and has been studied extensively in the past ten years. Our result generalizes and indeed builds upon the result from 1814 that polygons have common dissections (without hinges). We also extend our result to edge-hinged dissections of solid 3D polyhedra that have a common (unhinged) dissection, as determined by Dehn's 1900 solution to Hilbert's Third Problem. Our proofs are constructive, giving explicit algorithms in all cases. For a constant number of planar polygons, both the number of pieces and running time required by our construction are pseudopolynomial. This bound is the best possible even for unhinged dissections. Hinged dissections have possible applications to reconfigurable robotics, programmable matter, and nanomanufacturing.