Scientists 'knit' soft robotic wearables for easier design and fabrication

They could be used for applications like assistive gloves for the disabled.


Scientists have made considerable progress with soft robots used for assistive wearables, rehabilitative technologies and more. Powered by compressed air, they offer advantages over regular robots like sensing capabilities, soft touch, and high power-to-input ratios.

Designing and building them has been a challenge, however, due to the need for a manual design and fabrication pipeline that requires a lot of trial and error. Now, scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a new pipeline called "PneuAct" that uses computers and a special knitting process to design and digitally fabricate the soft pneumatic actuators. Their work could eventually lead to new assistive and rehabilitative devices.

"PneuAct uses a machine knitting process — not dissimilar to your grandma's plastic needle knitting — but this machine operates autonomously," according to CSAIL researchers. The designer simply needs to specify the stitch and sensor design patterns in software to program actuator movements, which can be simulated before printing. The textile piece is then fabricated by the knitting machine, which is fixed to a rubber silicone tube to complete the actuator.

The actuators use conductive yarn for sensing so they can essentially "feel" or respond to what they grab. As proof of concept, the team developed several prototypes including an assistive glove, soft hand, interactive robot and a pneumatic walking quadruped, as shown in the video above.

The new devices are considerably improved over older designs, incorporating programmed bending when inflated and the ability to incorporate feedback. "For example, the team used the actuators to build a robot that sensed when it was touched specifically by human hands, and reacted to that touch," the team wrote. The glove could be worn to supplement finger muscle movement, adding extra force for grasping to help people with finger or hand injuries.

The team plans to explore actuators with different shapes, and incorporate task-driven designs with target poses and optimal stitch patterns. "Our software tool is fast, easy to use, and it accurately previews users' designs, allowing them to quickly iterate virtually while only needing to fabricate once," said Harvard University's Andrew Spielberg, an author on the paper.