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Researcher Develops Bio-Inspired Technology Based on Bat’s Ear

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Image: Virginia Tech

Rolf Mueller, professor of mechanical engineering at Virginia Tech, has drawn inspiration from bats to design and develop a new bio-inspired technology that can determine the origin location of a sound. Unlike previous approaches, which are often based on the human ear, Mueller looked at a bat’s ear to gain the first new insight into identifying sound location in 50 years. 

“I have long admired bats for their uncanny ability to navigate complex natural environments based on ultrasound and suspected that the unusual mobility of the animal’s ears might have something to do with this,” he said. 

Mueller was joined by former Ph.D student and lead author Xiaoyan Yin. The findings were published in Nature Machine Intelligence.

Bat vs. Human Ear 

Bats rely on echolocation to navigate when flying, and it enables them to determine the distance of an object by listening to echoes as it sends out sounds. The bat’s mouth or nose emits ultrasonic calls, which bounce off the environment and return as an echo. Termed the Doppler effect, they can also extract information from ambient sounds.

This effect is different when it comes to humans, with our two ears enabling us to find location through sound data that goes to the brain for processing. By having two receivers, we can detect the direction of sounds when they contain only one frequency. 

In 1967, a discovery demonstrated that a single human ear can detect the location of sounds if there are different frequencies. 

The human ear has been the inspiration for various approaches to detecting sound location in the past, which have relied on pressure receivers like microphones and the ability to collect multiple frequencies. 

Mueller saw that there were greater possibilities with bat ears, which are far more versatile than human ears. His team set out to use a single frequency and single receiver instead of multiple. 

Mueller lab sound tracking

Developing the Technology

One of the first steps was to recreate the bat’s ability to move their ears, which they did by creating a soft synthetic ear attached to a string and simple motor. This system was timed with the ear fluttering whenever it received an incoming sound. 

The bats that served as an inspiration for the new technology have ears with a complete transformation of sound waves, which is based on the shape of the outer ear. This part of the bat’s ear uses the ear movement as it receives sound to create multiple shapes for reception, with the sound being channeled into the ear canal. 

One of the biggest challenges faced by the team was to extract readable and interpretable data from the incoming sound waves. In order to achieve this, they placed the ear above a microphone to create a similar mechanism to the bat. 

Because of the fast motions of the fluttering outer ear, Doppler shift signatures were created, and these related to the direction of the sound’s source. However, it was still not easy to interpret due to complex patterns. 

The team then turned towards a deep neural network, training it to provide the source direction with each echo received. 

The system was tested with the ear being mounted on a rotating rig, which included a laser pointer. A loudspeaker was then placed in different directions relative to the ear, and sounds were emitted. 

After determining the direction of the sound, the control computer rotated the system so the laser pointer hit a target on the loudspeaker, which resulted in the location being pinpointed within half a degree. This is impressive when compared to previous results, which have demonstrated that human ears usually determine location within 9 degrees, and state-of-the-art technology has only been able to pinpoint it within 7.5 degrees. 

“The capabilities are completely beyond what is currently in the reach of technology, and yet all this is achieved with much less effort,” said Mueller. “Our hope is to bring reliable and capable autonomy to complex outdoor environments, including precision agriculture and forestry; environmental surveillance, such as biodiversity monitoring; as well as defense and security-related applications.”

 

Alex McFarland is a historian and journalist covering the newest developments in artificial intelligence.