Researchers at Purdue University and the University of Tennessee have turned to an unusual source of inspiration for new drone wings capable of better handling potentially dangerous environments: the disposable lids on to-go cups.
"There’s this problem called ‘data drowning,'" explains Purdue associate professor of mechanical engineering Andres Arrieta, co-corresponding author of the paper detailing the novel wing design. "Drones cannot use their full flight capability because there is just too much data to process from their sensors, which prevents them from flying safely in certain situations."
The solution, then, is to filter out information the drone doesn't actually need — but in a way that won't discard information important to the safety of the flight. Rather than put that task onto a central processor or deep-learning accelerator, though, the team has built a "smart" wing, which uses a neuromorphic metamaterial to learn how to respond to environmental feedback on its own — using the raised bumps on to-go cup lids as their inspiration.
The wing developed by the researchers uses a series of raised domes, similar to those depressed on cup lids to indicate caffeinated versus decaf coffee or diet versus full-sugar soda. The domes can be flattened, but only when the forces applied exceed a certain minimum — automatically filtering out forces below this level. Depending on which domes are deformed and that remain, the drone's control system can be alerted to potentially dangerous forces and take action — without having to filter out the safe forces itself.
Based on the concept of "associative memory," the smart wing design could trigger evasive action in the event of an approaching obstacle or warn when certain temperature or pressure limits are exceeded — using memristor devices connected to the dome array.
While the study showed the material's potential, though, it could be some time before it takes to the air: Arrieta claims that it will be possible to build a functional flight-ready drone using the new wing technology within the next three to five years, but that additional work is required to test how the material responds to various environmental conditions. The team also suggests the technology could be applied to the fields of robotics, autonomous systems, and wearables.
The team's work has been published under open-access terms in the journal Advanced Intelligent Systems.