A to-go lid from a cup holds the secret to creating a safer drone wing

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A to-go lid from a cup holds the secret to creating a safer drone wing
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Researchers discovered a new use for the dome shape usually found on the top of plastic to-go cup lids.

like drones don’t have ways to filter information, in this case dangerous conditions, and therefore the response time is slowed down. “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.

A certain number of domes that either pop up or down at certain parts of the drone’s wings could suggest a dangerous pressure pattern by signaling the drone’s control system. Another example is using the domes to signal dangerous temperatures to the drone.The invertible domes could allow the drone wings to have a type of “memory” and eventually recognize dangerous conditions. This learning strategy is called associative memory or recalling parts of a memory to construct the complete version.

The research team noted that the domes can only be implemented in two ways — popped up or down. They figured the conditions could act as zeroes and ones to create spatial patterns for developing associative memory.The study showed that when a force inverts a dome in the drone’s wing, sensors embedded into the flat part of the material can distinguish the difference in shape.

With each dome, the metamaterial “learned” to remember the pattern of the level of force created on its exterior. The drone wing would be able to quickly recall such a pattern associated with dangerous conditions because the material would store the data as partial memories, or associative memories, from the inverted dome patterns. It would then put all this information together to create a full single memory.

The metamaterials combine engineering, memory and learning capabilities to create an advanced wing for drones with the ability to retain information that could change the future of UAVs.

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