Carnegie Mellon University (CMU) engineers have created a new software that can translate 3D shapes into step-by-step instruction for knitting machines.
The system, which was developed in the Carnegie Mellon Textiles Lab, could enable computer-controlled knitting machines to produce a variety of plush toys and garments.
Drawing light on this development, James McCann, assistant professor in the Robotics Institute and leader of the lab, said that the ability to generate knitting instructions without need of human expertise could make on-demand machine knitting possible.
McCann hopes to use the same machines that routinely crank out thousands of knitted hats, gloves and other apparel, to produce customized pieces one at a time or in small quantities.
“Knitting machines could become as easy to use as 3D printers,” contends McCann which is in stark contrast to the world of knitting today.
“Now, if you run a floor of knitting machines, you also have a department of engineers,” said McCann, noting that garment designers rarely have the specialized expertise necessary to program the machines. “It’s not a sustainable way of doing one-off customized pieces.”
McCann and his colleagues have thus developed a method for transforming 3D meshes – a common method for modeling 3D shapes – into instructions for V-bed knitting machines.
V-bed knitting machines manipulate loops of yarn with hook-shaped needles, which lie in parallel needle beds angled toward each other in an inverted V shape.
Such machines are highly capable, but are limited in comparison with hand knitting, says Vidya Narayanan, a Ph.D. student in computer science.
Narayanan asserts that the CMU algorithm takes these constraints into account, producing instructions for patterns that work within the limits of the machine and reduce the risk of yarn breaks or jams.
A front-end design system such as this is common in 3D printing and in computer-driven machine shops, but not in the knitting world, says McCann.
Likewise, 3D printing and machine shops use common languages and file formats to run their equipment, while knitting machines use a variety of languages and tools that are specific to particular brands of knitting machines.
This led McCann to create a common knitting format, called Knitout, which is capable of being implemented with any brand of knitting machine.
The newly developed system produces only smooth knitted cloth, without the patterned stitching that can make knitted garments distinctive. This could however change in the future, says McCann.
“The knitting hardware is already really good. It’s the software that needs a little push. And software can improve rapidly because we can iterate so much faster.”
Content and image; Carnegie Mellon University via Eurekalert/Michael Henninger