To teach the drone to herd autonomously, Soon-Jo Chung, an associate professor of aerospace, and his colleagues [...] studied and derived a mathematical model of flocking dynamics to describe how flocks build and maintain formations, how they respond to threats along the edge of the flock, and how they then communicate that threat through the flock. Their work improves on algorithms designed for herding sheep, which only needed to work in two dimensions, instead of three. Once they were able to generate a mathematical description of flocking behaviors, the researchers reverse engineered it to see exactly how approaching external threats would be responded to by flocks, and then used that information to create a new herding algorithm that produces ideal flight paths for incoming drones to move the flock away from a protected airspace without dispersing it. The team tested the algorithm on a flock of birds near a field in Korea and found that a single drone could keep a flock of dozens of birds out of a designated airspace. The effectiveness of the algorithm is only limited by the number and size of the incoming birds.
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