Soft pneumatic actuators may not be a phrase that comes up in everyday conversation, but more than likely you have benefited from their usefulness. The devices use compressed air to power movement, and with sensing capabilities they have proven to be an essential component in a variety of applications such as wearable assistive devices, robotics and rehabilitation technology. .
But there’s a bit of a bottleneck in creating small, dynamic devices that have advantages like high response rates and power-to-input ratios. They require a manual design and manufacturing pipeline, which results in many trial-and-error cycles to test and see if the designs will work.
Scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a scalable pipeline to computer-design and digitally manufacture flexible pneumatic actuators called “PneuAct”.
PneuAct uses a machine knitting process, not much different from your grandmother’s plastic needle knitting, but this machine works on its own. A human designer simply specifies the point and sensor design patterns in software to program the movement of the actuator, and it can then be simulated before printing. The textile part is made by the knitting machine, which can be attached to a cheap ready-made rubber silicone tube to complete the actuator.
The knitted actuator incorporates a conductive yarn for sensing, allowing actuators to “sense” what they are touching. The team concocted several prototypes covering a support glove, a soft hand, an interactive robot and a pneumatic walking quadruped. Their prototypes, which, using a yellow fabric somewhat resembling banana fingers, covered a support glove, a soft hand, an interactive robot and a pneumatic quadruped robot.
Although there has been a lot of movement in the hardware development of soft pneumatic actuators over the years – a 2019 prototype of a collaborative robot used such actuators to replicate a human-like grip in its hands – the design tools did not improve with such speed. Older processes typically used polymers and molding, but scientists have used a combination of elastic and sensing points (with a conductive thread) that allow the actuators to be programmed to flex when inflated and the ability to integrate a real-world feedback.
For example, the team used the actuators to build a robot that detected when it was hit specifically by human handsand reacted to this contact.
The team glove can be worn by a human to complement finger muscle movement, minimizing the amount of muscle activity required to complete tasks and movements. This could have a lot of potential for people with injuries, limited mobility or other finger trauma. The method can also be used to make an exoskeleton (wearable, computer-controlled robotic units that complement human movement and restore locomotion and motion); for example, the authors created a sleeve that can help wearers bend the elbow, knee, or other parts of the body.
“Using digital machine knitting, which is a very common manufacturing method in today’s textile industry, allows a design to be ‘printed’ in one go, making it much more scalable. says Yiyue Luo, Ph.D. MIT CSAIL. student and lead author of a new research paper. “Soft, tender pneumatic actuators are inherently compliant and flexible, and combined with smart materials, have become the backbone of many robots and assistive technologies – and rapid manufacturing with our design tool can hopefully increase ease and ubiquity .”
Giving meaning to sensors
One type of sensing the team incorporated was “resistive pressure sensing”, where the actuator “sends” the pressure. When making a robotic gripper, for example, when it grabs something, the pressure sensor detects the force applied to the object and then tries to see if the grip is successful or not. The other type is “capacitive sensing”, where the sensor discerns certain information about the materials the actuator comes into contact with.
Although the actuator was sturdy – no wires broke in any of their experiments, one of the limitations of the system was that it was limited to tube shaped actuators as it is very easy to buy off the shelf . A logical next step is to explore actuators of different shapes, to avoid being constrained by this unique structure. Another extension that scientists will explore is extending the tool to incorporate task-based optimization-based design, where users can specify target poses and optimal point patterns that can be automatically synthesized.
“Our software tool is quick and easy to use and accurately previews users’ designs, allowing them to quickly iterate virtually while only needing to manufacture once. But this process still requires some trial and error from from humans. Can a computer reason about how textiles should be physically programmed into actuators to enable rich, sensing-driven behavior? That’s the next frontier,” says Andrew Spielberg, postdoctoral fellow in materials science and mechanical engineering at Harvard University, another author of the article.
The document was published via the CHI Conference on Human Factors in Computing Systems.
Yiyue Luo et al, Digital fabrication of pneumatic actuators with integrated sensing by machine knitting, CHI Conference on Human Factors in Computing Systems (2022). DOI: 10.1145/3491102.3517577
Provided by MIT Computer Science and Artificial Intelligence Laboratory
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