Bats can fly through dense forests at night, avoiding trees, branches, and even other bats. While echolocation helps them do this, scientists have not fully understood how bats process the constant stream of echoes while flying through such complex environments.
Now, in a new study published in Proceedings of the Royal Society B, scientists from the University of Bristol reframe the concept of echolocation. Rather than analyzing each echo individually, researchers suggest that bats rely on a sound-guided sense of motion.
The new findings could have several potential applications and may even help to guide the design of future drones and autonomous vehicles.
A Sound-Based Version of Motion Perception
During echolocation, bats produce rapid, high-frequency calls and listen for the echoes returning from nearby objects. In open areas, this method works well. In cluttered settings such as forests, however, a single call can generate echoes from many surfaces at once, each arriving from a different direction and distance.
Sorting through each signal in real time would require a high processing speed, even for animals built for this task. Researchers have suspected that bats use a different strategy that limits sensory overload while still allowing them to accurately control their movements.
The study focuses on a concept called acoustic flow velocity. As bats fly forward, they send out vocal calls. The echoes from these calls reach their ears at different speeds, depending on how close objects are and how quickly the bat is moving. These changing echoes create a steady sound pattern that bats use to steer while flying.
“A single bat call will return echoes from multiple objects in different directions and distances,” said lead author Dr. Athia Haron. “For them to analyse each individual echo becomes too difficult, so they rely on alternative navigational strategies.”
The ‘Bat Accelerator’ Experiment
The research team built a custom experimental setup they dubbed a “bat accelerator machine.” The system consisted of an eight-meter flight corridor lined with hedge-like panels containing roughly 8,000 artificial acoustic reflectors designed to mimic the echoes produced by natural vegetation.
The reflectors could be rotated to move with or against the bat’s direction of travel. This allowed the researchers to alter the acoustic flow the bat experienced while keeping the corridor’s physical layout unchanged.
Over three nights, the team recorded 181 flight trajectories from wild pipistrelle bats. Of those, 104 flights were included in the final analysis.
Sound Influences Speed
The results showed that when the reflectors moved against the bats’ flight direction, creating a faster-than-normal acoustic flow, the bats slowed down. When the reflectors moved in the same direction as the bats, which reduced the acoustic flow, the bats sped up.
Sometimes, the bats changed their speed by as much as 28%. These changes happened even though their movement through the air did not change. This indicates that changes in sound alone were sufficient to influence the bats’ flight speed. The results suggest that bats can sense changes in their echoes and automatically adjust their speed.
Biomimetic Applications
This discovery has applications beyond biology. Engineers have struggled to design autonomous systems that can move safely in dark, crowded, or blocked spaces. Systems that rely on detailed maps for navigation often do not work well in these environments.
This research could be used to develop a new navigation strategy inspired by biology. The authors suggest that Doppler-based acoustic flow could enable new ways to guide drones, especially in crowded, hard-to-see places. Adapting and emulating concepts from nature to solve complex human challenges like this is often referred to as biomimicry.
The experiments were conducted in a controlled corridor and involved only one bat species. More testing in real-world settings will be required to apply acoustic flow strategies to engineering. Still, the study demonstrates how biological systems can solve complex problems by using efficient shortcuts instead of gathering more data.
Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds a Master of Business Administration, a Bachelor of Science in Business Administration, and a Data Analytics certification. His work combines analytical training with a focus on emerging science, aerospace, and astronomical research.