Spec2Fab: A reducer-tuner model for translating specifications to 3D prints
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Matusik_Spec2Fab.pdf
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3.55 MB
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Author(s)
Chen, Desai
Didyk, Piotr
Sitthi-Amorn, Pitchaya
Matusik, Wojciech
Levin, David
Date Issued
July 2013
Journal
ACM Transactions on Graphics
Publisher
Association for Computing Machinery (ACM)
Citation
Desai Chen, David I. W. Levin, Piotr Didyk, Pitchaya Sitthi-Amorn, and Wojciech Matusik. 2013. Spec2Fab: a reducer-tuner model for translating specifications to 3D prints. ACM Trans. Graph. 32, 4, Article 135 (July 2013), 10 pages.
Version
Author's final manuscript
Abstract
Multi-material 3D printing allows objects to be composed of complex, heterogenous arrangements of materials. It is often more natural to define a functional goal than to define the material composition of an object. Translating these functional requirements to fabri-cable 3D prints is still an open research problem. Recently, several specific instances of this problem have been explored (e.g., appearance or elastic deformation), but they exist as isolated, monolithic algorithms. In this paper, we propose an abstraction mechanism that simplifies the design, development, implementation, and reuse of these algorithms. Our solution relies on two new data structures: a reducer tree that efficiently parameterizes the space of material assignments and a tuner network that describes the optimization process used to compute material arrangement. We provide an application programming interface for specifying the desired object and for defining parameters for the reducer tree and tuner network. We illustrate the utility of our framework by implementing several fabrication algorithms as well as demonstrating the manufactured results.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2461912.2461994
