In the GIF below, we see Bluebots trying a different task: a search mission. This behavior is a bit more complex, guided by a few separate guidelines in the algorithm. The first step is known as dispersion; the algorithm ensures that the robots stay away from each other. This scatters them in search of their target, a red LED on the bottom of the tank. “If they all spread out and maximize their distances, they get better coverage and are more likely to find the source,” Berlinger says.
When a Bluebot trips on the red LED, it starts flashing its own blue LEDs, a signal to its comrades that it has found the target. When another robot sees the blinking blue, its algorithm switches from the dispersion directive to an aggregation directive, which gathers the robots around the target. “As soon as they see the source themselves, they also start flashing their LEDs to amplify the signal,” says Berlinger. “Parallel actions can speed up that search mission enormously. If a single robot had to search for the source, it would take about 10 times as long as the seven robots. “
This is the power of the masses: a team of Bluebots in constant communication – and an extraordinarily simple form of communication – can work together to accomplish a mission. “I find it an extremely challenging problem to do these experiments,” said roboticist Robert Katzschmann of the research university ETH Zurich, who developed his own robotic fish but was not involved in this new research. “So I’m really impressed with the fact that they set this up because it looks much easier than it actually is.”
“Now,” adds Katzschmann, “the question is, do real fish really do it this way?” Vision is certainly an important tool for schooling fish, but like other animals, their perception is ‘multimodal’. That is, their vision works in tandem with their other senses, in this case a fish organ known as the sideline. This line of sensory cells, running down the sides of a fish from head to tail, detects subtle changes in water pressure, which could complement his vision to keep him in sync with his fellows as the school moves.
However, it is clear that these researchers have achieved impressively complex swarming behavior using vision alone. And as cameras become cheaper and more sophisticated, the researchers can give their Bluebots an increasingly rich picture of their environment. “I would really like to get rid of the blue LEDs and go to literally just patterns on the fish, and be able to do more,” said Harvard roboticist Radhika Nagpal, a co-author of the paper. Maybe one day the Bluebot will be able to hit the high seas, where it must visually detect obstacles such as coral in order not to crash. It might even look for invasive species like the lionfish by looking for its signature stripe morphology, as it hasn’t yet developed LEDs to guide the Bluebot.