Protecting critical infrastructure such as airports from unwelcome aerial trespassing has been a major, longstanding area of focus for aviation authorities and law enforcement. With stunning affordability and exceptional ease of use in this modern drone landscape of ours, near-misses between UAVs and commercial aircraft have risen sharply. But it’s not just the motorized aerial entities threatening to put aircraft and their passengers in danger, as birds can do quite a lot of damage, too.
According to the California Institute of Technology (Caltech), herding birds away from airports, ironically by using a drone-specific algorithm to do so, has been the primary focus of four brilliant Caltech engineers. In a study titled “Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle,” which was recently published in IEEE Transactions on Robotics, the team explained how its algorithm works, the potential ramifications of its success, and what inspired this project in the first place.
Soon-Jo Chung, part of the team and researcher at Caltech’s Center for Autonomous Systems and Technologies (CAST), explained that previous methods, such as training falcons to scare flocks of birds away or using manually piloted drones to do so, are either costly or unreliable.
“When herding birds away from an airspace, you have to be very careful in how you position your drone,” said Chung. “If it’s too far away, it won’t move the flock. And if it gets too close, you risk scattering the flock and making it completely uncontrollable. That’s difficult to do with a piloted drone.”
The most important factor in effectively managing a flock of birds and herding it in a controlled direction is forcing it to behave as one contained group. If you scatter the flock, each bird flies off in an undetermined direction, which could potentially result in even more disastrous consequences than previously thought.
Fortunately, each bird reacts to the behavioral changes of the bird closest to it, which essentially means introducing an external threat successfully to one bird, results in a domino effect that causes every remaining bird to behave similarly. This, of course, required absolutely precise drone positioning and a reliable algorithm to produce those results every single time.
Let’s take a look, shall we?
Together with his former graduate students and colleagues, including Aditya Paranjape of Imperial College London, Chung observed and analyzed a mathematical model of the dynamics of bird flocks. This taught them how flocks come together, maintain their formations, and how exactly they respond to external threats on the perimeters of their flock.
“We carefully studied flock dynamics and interaction between flocks and pursuers to develop a mathematically sound herding algorithm that ensures safe relocation of flocks using autonomous drones,” said Kyunam Kim, co-author of the IEEE research paper and postdoctoral scholar in aerospace at Caltech.
Once the mathematical representation showed researchers how bird flocks naturally responded to said threats, the team was able to reverse engineer this information to develop the resulting herding algorithm. Though it sounds fairly simple, once described in a linear, detailed fashion from some of the most brilliant young minds in engineering, this is clearly an extremely sophisticated system, and one that could have enormous ramifications for those eager to protect important airspace and critical infrastructures.
This algorithm was tested successfully on a flock of birds in Korea, with the results showing that a single autonomous drone could effectively re-route a flock of dozens of birds. Chung said that the algorithm is reliable, depending on the size and number of birds, and that the team is eager to scale the project up. Upcoming iterations would be focused on using multiple drones simultaneously for multiple flocks of birds. What is most impressive here, is that we’re on the verge of seeing an entirely new preventative measure regarding valuable property and bird incursions, which would see autonomous drones successfully re-route flocks without much, if any, manual input required.