A Compiler for 3D Machine Knitting
Jim McCann (Disney Research Pittsburgh)
Lea Albaugh (Disney Research Pittsburgh)
Vidya Narayanan (Disney Research Pittsburgh)
April Grow (Disney Research Pittsburgh)
Wojciech Matusik (Massacusetts Institute of Technology)
Jen Mankoff (Disney Research Pittsburgh, Carnegie Mellon University)
Jessica Hodgins (Disney Research Los Angeles, Disney Research Pittsburgh)
ACM SIGGRAPH 2016
July 24, 2016
Industrial knitting machines can produce finely detailed, seamless, 3D surfaces quickly and without human intervention. However, the tools used to program them require detailed manipulation and understanding of low-level knitting operations. We present a compiler that can automatically turn assemblies of high-level shape primitives (tubes, sheets) into low-level machine instructions. These high-level shape primitives allow knit objects to be scheduled, scaled, and otherwise shaped in ways that require thousands of edits to low-level instructions. At the core of our compiler is a heuristic transfer planning algorithm for knit cycles, which we prove is both sound and complete. This algorithm enables the translation of high-level shaping and scheduling operations into needle-level operations. We show a wide range of examples produced with our compiler and demonstrate a basic visual design interface that uses our compiler as a backend.
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