Researchers at MIT demonstrated gloves fabricated by a system for automating knitted garments. Image: MIT CSAIL

Researchers at MIT demonstrated gloves fabricated by a system for automating knitted garments. Image: MIT CSAIL

Researchers in the US have developed a new system and design tool for programming high-tech knitting machines and customising knitted patterns and shapes – in a move that could help non-experts design and even customise their own garments. 

Detailed in two new papers, researchers from Massachusetts Institute of Technology's (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL) have outline their new approach to streamline computer-aided knitting. 

'InverseKnit' translates photos of knitted patterns into instructions that are then used by the knitting machines to make clothing. An approach like this could enable casual users to create designs without coding knowledge, and even reconcile issues of efficiency and waste in manufacturing, MIT says.  

"As far as machines and knitting go, this type of system could change accessibility for people looking to be the designers of their own items,'' says Alexandre Kaspar, CSAIL PhD student and lead author on a new paper about the system. "We want to let casual users get access to machines without needed programming expertise, so they can reap the benefits of customisation by making use of machine learning for design and manufacturing." 

To get InverseKnit up and running, the team first created a dataset of knitting instructions and the matching images of those patterns. They then trained their deep neural network on that data to interpret the 2D knitting instructions from images. When testing InverseKnit, the team found that it produced accurate instructions 94% of the time. 

Meanwhile, in another paper, researchers unveiled details of a new computer-aided design tool for customising knitted items. The tool lets non-experts use templates for adjusting patterns and shapes, such as adding a triangular pattern to a beanie, or vertical stripes to a sock. 

While there have been plenty of developments in the field, the distortions inherent in 3D shapes can sometimes hamper positioning details which can be a burden on designers.  To address this design issue, Kaspar and his colleagues developed a tool called 'CADKnit' which uses 2D images, CAD software, and photo editing techniques to let casual users customise templates for knitted designs.

"Whether it's for the everyday user who wants to mimic a friend's beanie hat or a subset of the public who might benefit from using this tool in a manufacturing setting, we're aiming to make the process more accessible for personal customisation," says Kaspar. 

The team tested the usability of CADKnit by having non-expert users create patterns for their garments and adjust the size and shape. In post-test surveys, the users said they found it easy to manipulate and customise their socks or beanies but lace patterns were tricky to design correctly and would benefit from fast realistic simulation.

However the system is only a first step towards full garment customisation, MIT notes. The authors found that garments with complicated interfaces between different parts – such as sweaters – did not work well with the design tool. 

"The impact of 3-D knitting has the potential to be even bigger than that of 3-D printing. Right now, design tools are holding the technology back, which is why this research is so important to the future," says McCann.