In the GIF below, we see Bluebots trying out another task – a Research 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 orders the robots to move away from each other. This spreads them out looking for their target, a red LED at the bottom of the tank. “If they all spread out and maximize their distances, they get better coverage and the chance of finding the source increases,” says Berlinger.
When a Bluebot lands on the red LED, it begins to flash 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 a scatter directive to an aggregation directive, which collects the robots around the target. “Once they see the source themselves, they also start blinking their LEDs to boost the signal,” says Berlinger. “Parallel actions can considerably accelerate this research mission. If a single robot were to search for the source, it would take about 10 times longer than the seven robots. “
That’s the power of the crowd: a team of Bluebots in constant communication – and an extremely simple form of communication, on top of that – can work together to accomplish a mission. “I find it extremely difficult to do these experiments,” says robotics Robert Katzschmann of the ETH Zurich research university, who developed his own robotic fish but was not involved in this new research. “So I’m very impressed with having it set up, because it looks a lot easier than it actually is.”
“Now,” adds Katzschmann, “the question is, do real fish really do it that way?” Vision is certainly an important tool for the education of fish, but like other animals, their detection is “multimodal”. That is, their vision works in concert with their other senses, in this case a fish organ known as the Lateral line. This line of sensory cells, which runs from head to tail along a fish’s sides, senses subtle changes in water pressure, which could complement its vision to help it stay in sync with his classmates while the school is on the move.
Clearly, however, these researchers have accomplished swarm behavior of impressive complexity with vision alone. And as cameras become cheaper and more sophisticated, it will allow researchers to give their Bluebots an increasingly richer picture of their surroundings. “I would really like to get rid of the blue LEDs and literally switch to having patterns on fish, and be able to do more,” says Radhika Nagpal, Harvard Robotics, co-author of the journal. Perhaps one day the Bluebot can hit the high seas, where it will have to visually detect obstacles like coral, so as not to crash. It might even look for invasive species like lionfish by looking for its distinctive frilly morphology, because it has not yet upgraded the LEDs to guide the Bluebot.