Researchers from MIT’s Computer Science and Artificial Intelligence Lab present the latest advancements in 3D printing at SIGGRAPH 2013.
With recent advances in three-dimensional (3D) printing technology, it is now possible to produce a wide variety of 3D objects, utilizing computer graphics models and simulations. But while the hardware exists to reproduce complex, multi-material objects, the software behind the printing process is cumbersome, slow and difficult to use, and needs to improve substantially if 3D technology is to become more mainstream.
On July 25, a team of researchers from the MIT Computer Science and Artificial Intelligence Lab (CSAIL) will present two papers at the SIGGRAPH computer graphics conference in Anaheim, California, which propose new methods for streamlining and simplifying the 3D printing process, utilizing more efficient, intuitive and accessible technologies.
“Our goal is to make 3D printing much easier and less computationally complex,” said Associate Professor Wojciech Matusik, co-author of the papers and a leader of the Computer Graphics Group at CSAIL. “Ours is the first work that unifies design, development and implementation into one seamless process, making it possible to easily translate an object from a set of specifications into a fully operational 3D print.”
3D printing poses enormous computational challenges to existing software. For starters, in order to fabricate complex surfaces containing bumps, color gradations and other intricacies, printing software must produce an extremely high-resolution model of the object, with detailed information on each surface that is to be replicated. Such models often amount to petabytes of data, which current programs have difficulty processing and storing.
To address these challenges, Matusik and his team developed OpenFab, a programmable “pipeline” architecture. Inspired by RenderMan, the software used to design computer-generated imagery commonly seen in movies, OpenFab allows for the production of complex structures with varying material properties. To specify intricate surface details and the composition of a 3D object, OpenFab uses “fablets”, programs written in a new programming language that allow users to modify the look and feel of an object easily and efficiently.
“Our software pipeline makes it easier to design and print new materials and to continuously vary the properties of the object you are designing,” said Kiril Vidimče, lead author of one of the two papers and a PhD student at CSAIL. “In traditional manufacturing most objects are composed of multiple parts made out of the same material. With OpenFab, the user can change the material consistency of an object, for example designing the object to transition from stiff at one end to flexible and compressible at the other end.”
Thanks to OpenFab’s streaming architecture, data about the design of the 3D object is computed on demand and sent to the printer as it becomes available, with little start-up delay. So far, Matusik’s research team has been able to replicate a wide array of objects using OpenFab, including an insect embedded in amber, a marble table and a squishy teddy bear.
In order to create lifelike objects that are hard, soft, reflect light and conform to touch, users must currently specify the material composition of the object they wish to replicate. This is no easy task, as it’s often easier to define the desired end-state of an object -- for example, saying that an object needs to be soft -- than to determine which materials should be used in its production.
To simplify this process, Matusik and his colleagues developed a new methodology called Spec2Fab. Instead of requiring explicit design specifications for each region of a print, and testing every possible combination, Spec2Fab employs a “reducer tree”, which breaks the object down into more manageable chunks. Spec2Fab’s “tuner network” then uses the reducer tree to automatically determine the material composition of an object.
By combining existing computer graphics algorithms, Matusik’s team has used Spec2Fab to create a multitude of 3D prints, creating optical effects like caustic images and objects with specific deformation and textural properties.
“Spec2Fab is a small but powerful toolbox for building algorithms that can produce an endless array of complex, printable objects,” said Desai Chen, a PhD student at CSAIL and lead author of one of the papers presented at SIGGRAPH.
The two papers to be presented at SIGGRAPH are “OpenFab: A Programmable Pipeline for Multi-Material Fabrication,” authored by Kiril Vidimče, Szu-Po Wang, Jonathan Ragan-Kelley and Wojciech Matusik; and “Spec2Fab: A Reducer-Tuner Model for Translating Specifications to 3D Prints,” authored by Desai Chen, David I. W. Levin, Piotr Didyk, Pitchaya Sitthi-Amorn and Wojciech Matusik.
Source: MIT Computer Science and Artificial Intelligence Lab