Soft robots can outshine their rigid counterparts in a whole variety of ways—for example, squeezing through tight spaces or sensing and carefully interacting with their surrounding environment.
To be useful in real-world applications, however, a soft robot typically requires many sensors to provide information about what the robot is doing—as well as its overall state, such as whether it’s bending, stretching, twisting or being compressed.
In general, adding more sensors to get better status information also dramatically increases the computation, data acquisition, and signal processing load.
“Each sensor requires electronic circuitry, so there are a lot of wires that need to go into the soft robot system,” says Michael Wehner, who joined the University of Wisconsin-Madison as an assistant professor of mechanical engineering in January 2022. “In addition, you need a lot of processing power, because each dedicated channel needs to feed back to a controller and requires significant signal processing and computation before you can use the signal. So, you need big data acquisition systems and this adds to the cost and complexity of the soft robot system.”
Now, Wehner and his collaborators have developed a system of passive sensors that can sense the entire state of a soft robot with less cost and complexity.