Author: Chloe O'Neal — Staff Writer
Date: August 15th, 2025
Scientists have long borrowed from nature to design technology. Animals have had hundreds of years to solve their own complex problems. Through studying them, researchers can develop technology that will help humans grapple with our own pressing issues. Right now, one of these emerging issues is developing simple, self-propelled robots that can perform collective, complex tasks with as simple directions as possible. This field of study is known as active matter, and a group of scientists based out of Penn State have chosen to model the bees. Swarm-like insects like bees use the collective sounds of their swarm to communicate with each other and navigate their environments. By using acoustic waves, scientists have created a model that reproduces this behavior in tiny robots they call swarmers. These swarmers are capable of self-organization, long-range transformation and real-time adaptation to environmental changes.
The researchers' plan was simple: develop micro-sized robots that communicate and self-organize via sound. To do this, they developed a computer model to simulate their experiment. In the model, each mini-robot was represented by an agent, and these agents are referred to as the swarmers.
Swarmers were given a few abilities to make the experiment possible. They can self-propel—move about the environment independently—and they can detect and emit sound. For the purposes of the study, the scientists focused on three types of sounds: acoustic signals, electromagnetic waves and surface waves.
They then gave the swarmers the ability to synchronize their frequencies and gave them two simple rules: "move towards larger sounds" and "change how you emit sound based on what sounds you hear." The swarmers were found to migrate towards the strongest signal.
The scientists then observed the interplay between the agents and the sounds they emitted, and how their movements adapted to the sounds they heard. Here's what they learned:
Agents Can Form A Spontaneous Variety of Shapes
The agents were able to self-organize into a variety of shapes, including snakelike structures, blobs and closed rings. Additionally, they found that these shapes all emitted different frequencies, so that each shape could be identified by their unique emission.
The shapes were also able to communicate with each other and make collective decisions about their environment. For example, in one test, researchers found that two similar-sized shapes were able to identify each other's position and successfully avoid bumping into each other by responding to the other's acoustic signals. These signals worked like a wall, helping the shapes to determine their own positions and the obstacles within the environment. The individual agents within the shapes were able to communicate this information with each other, and then make a collective decision about how to move around the environment. This type of collective decision-making tended to grow stronger with the more agents in a group, as single agents can only emit a smaller sound. By working together, the swarmers were able to gather more information at a faster rate, and subsequently react faster to that information.
In a similar scenario, the agents were even able to regroup or "self-heal" after encountering an obstacle designed to forcibly disrupt their formation. The snakelike structure came upon a thin hole, which researchers surmised would only allow a handful of the collective through. However, the agents that were temporarily disengaged along the way eventually made their way through the hole, and reconnected with the larger structure after passing through.
Researchers also found that the swarmers' positioning and general structures could be manipulated by external sounds introduced into the experiment.
A Small Step Towards A Greater Understanding Of Active Matter
This is the first time scientists have explored a sound-driven approach to manipulating active matter. Active matter studies the collective movement of self-propelled agents through biological or synthetic means. In chemical-based studies, agents were manipulated with chemical signals. Though these attempts were successful in producing collective behavior and self-organization, chemical signals perform significantly slower than acoustic signals. This is primarily because information transmission relies on how far and fast the chemical signals can spread, and on how quickly agents can react to and emit their own signals in response.
With acoustic-based signals, sound waves are more robust: they can travel greater distances at faster speeds, and can be administered remotely or even reversed, enabling a greater degree of range and possibilities for application.
Potential Applications
The potential applications for acoustic signal active matter are numerous. The researchers believe the agents could be used to help clean up ocean pollution, detect future sources for pollution, and be deployed in the human body to help deliver specific treatment to specific parts.
As research continues, scientists will have to explore how to engineer the robots to facilitate more complex audio processing, such as interpreting multiple sounds in a single environment, or navigating areas populated with organisms capable of absorbing acoustic waves.
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