Bat-like robotic sonar system 'more efficient'

A dynamic sonar system inspired by horseshoe bats which could take up less space than current man-made sonar arrays has been built by engineers at Virginia Tech.

Bats use biological sonar, called echolocation, to navigate and hunt, and horseshoe bats are especially skilled at using sounds to sense their environment.

“Not all bats are equal when it comes to biosonar", said Rolf Müller, a mechanical engineer at Virginia Tech.

“Horseshoe bats hunt in very dense forests and they are able to navigate and capture prey without bumping in to anything.

“In general, they are able to cope with difficult sonar-sensing environments much better than we currently can.”

Müller and his team examined the ears and noses of bats in the lab and by using motion-capture technology they revealed that the bats rapidly deform their outer ear shapes to filter sounds based on frequency and direction to serve different sensing tasks.

“They can switch between different ear configurations in only a tenth of a second - three times faster than a person can blink their eyes,” said Philip Caspers, a graduate student in Müller’s lab.

Unlike bat species that employ a less sophisticated sonar system, horseshoe bats emit ultrasound squeaks through their noses rather than their mouths.

Using laser-Doppler measurements that detect velocity, the team showed that the noses of horseshoe bats also deform during echolocation, much like a megaphone whose walls are moving as the sound comes out.

The team applied their findings to develop a robotic sonar system that incorporates two receiving channels and one emitting channel, which are able to replicate some of the movements of the bat’s ears and nose.

In comparison, modern naval sonar arrays can have receivers that measure several metres across and have many hundreds of separate receiving elements for detecting incoming signals.

By reducing the number of elements in their prototype, the team hopes to create small, efficient sonar systems that use less power and computing resources than current arrays.

“Instead of getting one huge signal and letting a supercomputer churn away at it, we want to focus on getting the right signal,” Müller said.

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