• June 28, 2022

Adorable Fish Bots Get Schooled in How to Swarm

Seven little Bluebots gently swim around a darkened tank in a Harvard University lab, spying on one another with great big eyes made of cameras. They’re on the lookout for the two glowing blue LEDs fixed to the backs and bellies of their comrades, allowing the machines to lock on to one another and form schools, a complex emergent behavior arising from surprisingly simple algorithms. With very little prodding from their human engineers, the seven robots eventually arrange themselves in a swirling tornado, a common defensive maneuver among real-life fish called milling.

Bluebot is the latest entry in a field known as swarm robotics, in which engineers try to get machines to, well, swarm. And not in a terrifying way, mind you: The quest is to get schools of Bluebots to swarm more and more like real fish, giving roboticists insights into how to improve everything from self-driving cars to the robots that may one day prepare Mars for human habitation.

Here’s how Bluebot works. Those eyeball cameras, which give the robot nearly 360-degree vision, are constantly searching for the blue LEDs of its neighbors, which on each robot are situated 86 millimeters apart. With this simple information, each Bluebot can determine its distance from another robot: If a neighbor is close, those two LEDs will appear to be far apart; if a neighbor is far away, the LEDs will appear to be closer. (The robot doesn’t roll or pitch, so the LEDs are always stacked vertically.) “Just by observing how far or close they are in a picture, they know how far or close the robot must be in the real world,” says Harvard biologist Florian Berlinger, lead author on a new paper in Science Robotics describing the work. “That’s the trick we play here.”

Video: Berlinger et al., Sci Robot. 6, eabd8668 (2021)

Once the robots are aware of the positions of their peers, Berlinger and his colleagues can then feed this positional information into simple algorithms to guide the behavior of the seven Bluebots dropped into a tank. For instance, to replicate the milling behavior, the researchers tell the Bluebots to just look at what’s going on in front of them. “The rule was: If there is at least one robot in front of you, you turn slightly to the right,” says Berlinger. “If there is no robot in front of you, you turn slightly to the left.” One by one, the Bluebots fall into line, as you can see in the GIF above.

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In the GIF below, we see Bluebots trying another task: a search mission. This behavior is a bit more complex, guided by a few separate directives in the algorithm. The first step is known as dispersion; the algorithm directs the robots to keep away from one another. This spreads them out 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 the chance that they find the source increases,” says Berlinger.

Video: Berlinger et al., Sci Robot. 6, eabd8668 (2021)

When one Bluebot stumbles on the red LED, it starts flashing its own blue LEDs, a signal to its comrades that it’s found the target. When another robot sees the flashing blue, its algorithm switches from the dispersal directive to an aggregation directive, which gathers the robots around the target. “Once they see the source themselves, they also start blinking their LEDs to reinforce the signal,” says Berlinger. “Parallel actions can speed up that search mission tremendously. If a single robot had to search for the source, it would take approximately 10 times as long as the seven robots.”

This is the power of the crowd: A team of Bluebots in constant communication—and an exceedingly simple form of communication, at that—can work together to accomplish a mission. “I find it an extremely challenging problem to do these experiments,” says roboticist Robert Katzschmann of the research university ETH Zürich, who has developed his own robotic fish but wasn’t involved in this new research. “So I’m very impressed by them having set this up, because it looks much easier than it actually is.”

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