Scientists ‘knit’ soft robotic clothes for easier design and manufacture

Scientists have made tremendous progress with soft robots used for wearable assistive devices, rehabilitation technologies and more. Powered by compressed air, they offer advantages over ordinary robots, such as sensing capabilities, soft touch and high power-to-input ratios.

However, their design and construction has been a challenge due to the need for a manual design and manufacturing pipeline that requires extensive trial and error. Now, scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new pipeline called “PneuAct” that uses computers and a special knitting process to digitally design and manufacture the flexible pneumatic actuators. Their work could eventually lead to new assistive and rehabilitative devices.

“PneuAct uses a machine knitting process – not much different from knitting with your grandmother’s plastic needle – but this machine works on its own,” according to the CSAIL researchers. The designer simply needs to specify the point and sensor design patterns in the software to program the actuator movements, which can be simulated before printing. The textile piece is then made by the knitting machine, which is attached to a silicone rubber tube to complete the actuator.

Actuators use a conductive thread for sensing so they can essentially “smell” or respond to what they catch. As a proof of concept, the team developed several prototypes, including a support glove, a soft hand, an interactive robot, and a pneumatic-walking quadruped, as seen in the video above.

The new devices are vastly improved over older designs, incorporating programmed flex when inflated and the ability to incorporate feedback. “For example, the team used the actuators to build a robot that detected when it was specifically touched by human hands and reacted to that touch,” the team wrote. The glove can be worn to complement finger muscle movement, adding extra grip strength to help those with finger or hand injuries.

The team plans to explore actuators of different shapes and incorporate task-oriented designs with target poses and optimal dot patterns. “Our software tool is fast, easy to use, and it accurately previews user designs, allowing them to quickly iterate virtually while only needing to manufacture once,” said Andrew Spielberg of the University. of Harvard, author of the article.

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Abdul J. Gaspar