Small domes on drones could act as danger sensors


The small domes that on to-go cup lids may one day save a winged drone from a nosedive, after US researchers tested a metamaterial that detects changes in pressure.

Patterns of the invertible domes on a drone’s wings would give it a way to remember in microseconds what dangerous conditions feel like and react quickly. The study, conducted by researchers at Purdue University and the University of Tennessee, Knoxville, is among the first demonstrations of a metamaterial that uses its shape to learn how to adapt to its surroundings on its own. The paper is published in the journal Advanced Intelligent Systems.

Unlike humans and other living beings, autonomous vehicles lack ways to filter out information they don’t need, which slows their response time to changes in their environment.

“There’s this problem called data drowning. 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,” said Andres Arrieta, a Purdue associate professor of mechanical engineering with a courtesy appointment in aeronautical and astronautical engineering.

Dome-covered surfaces that can sense their surroundings would be a step toward enabling a drone’s wings to feel only the most necessary sensory information. Because it only takes a certain minimum amount of force to invert a dome, forces below this threshold are automatically filtered out.

A specific combination of domes popping up and down at certain parts of the wing, for example, could indicate to the drone’s control system that the wing is experiencing a dangerous pressure pattern. Other dome patterns could signify dangerous temperatures or that an object is approaching, Arrieta said.

wing with domes

Arrays of domes on a drone wing may help it detect information from its surroundings only when necessary. (Image: Purdue University / Jared Pike)

Giving drones associative memory through feel

For decades, electronics have been designed to save and retrieve images by encoding information in patterns of black or white pixels as zeroes or ones. Because a dome can adopt only two states — popped up or popped down — these states can act like zeroes and ones to create spatial patterns for building associative memory.

Arrieta and his team showed in the study that when a certain level of force inverts a dome, sensors embedded into the flat part of a metamaterial sheet surrounding the dome detect the change in shape. An electrical signal then triggers a memory device called a memristor to make a record of the force and where it was detected on the sheet. With each instance of an inverted dome, the metamaterial learns to remember the pattern that a certain level of force creates on its surface.

In practice, a drone wing would be able to quickly recall a pattern associated with a dangerous condition because the metamaterial keeps a record of all its “partial memories” from inverted dome patterns as a single “complete memory” that these patterns create altogether. Based on this study, the researchers believe that the metamaterial wouldn’t need to “buffer” to recall information that it stores within itself over time.

Since the metamaterial can be manufactured with existing methods, these domes can easily cover a large surface area like a drone’s wing, Arrieta said. Next, the researchers will test how the material responds to its surroundings based on information it learns from the domes. Arrieta anticipates that it will be possible to build a drone wing using this material design in the next three to five years.


This article was written by Kayla Wiles and originally published by Purdue University.

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Ben has worked as a journalist and editor, covering technology, engineering and industry for the last 20 years. Initially writing about subjects from nuclear submarines to autonomous cars to future design and manufacturing technologies, he was editor of a leading UK-based engineering magazine before becoming editor of Aerospace Testing in 2017.

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