Team drew inspiration from mathematical principles
A team from the University of Buffalo is looking into how drones can be programmed to map an oil spill using mathematical principles.
In a computer simulation, five drones working together mapped an oil spill spanning nearly a kilometre wide in just nine minutes.
“Nature may not proactively use mathematics, nor does it have foresight. It behaves in ways driven by feedback, implicit drive for adaptation, and a certain degree of apparent randomness,” said Souma Chowdhury, PhD, assistant professor of mechanical and aerospace engineering in the University at Buffalo’s School of Engineering and Applied Sciences.
“But we can look at what kind of mathematical principles define that behaviour. Once we have that, we can use it to solve very complex problems,” he continued.
Chowdhury has pioneered a way to programme drones to quickly map an oil spill. His efforts were published in a paper which he co-authored with students Zachary Ball and Philip Odonkor. The study optimised and simulated a five-drone swarm that can map a nearly one-kilometre wide spill in nine minutes.
To achieve that, Chowdhury had to overcome the lack of communication bandwidth typical of a flying ad hoc network and the short battery life of off-the-shelf drones.
Following the principles partly inspired by a flock of birds, he devised a way for the drones to quickly record whether they are over water, oil or the edge of the spill. In addition, the drones assumed that the space around the oil they have spotted is also oil, although that is recorded as less than certain. This information is shared with the other drones, as opposed to sharing actual images or video, which would require too much bandwidth.
As the drones move from point to point over the spill, they avoid going over space that other drones have already covered. With five drones making observations every five seconds, the size of the spill can be determined quickly.
The drones also fly to their base, on a boat, when their batteries get low. The drones that replace them would have the information from the other drones, so they avoid previously mapped locations.
“The thematic focus of my lab is developing computational design approaches that take inspiration from nature,” Chowdhury said, adding that there was no need for human interaction during the mission.
His approach uses simple, affordable drones that are accessible to many people. “This task can be accomplished by off-the-shelf drones that cost under $1,000. All they need is to have a simple drone-mountable camera system and use our software,” he said. The low computer power — each drone can operate with a $35 Raspberry Pi computer — also helps to keep costs low.
Collision avoidance is another challenge. Here, Chowdhury drew inspiration from nature. A recent study by the University of Queensland discovered how parrots avoided crashing into one another by observing a simple rule of always veering to the right. Thus, his lab is exploring how drones can pre-emptively turn a certain angle to the right upon sensing another member of the swarm.
In addition to oil spills, swarming drones could be used in forest fires or other natural disasters. By changing the cameras on the drones, they may also be used to locate people trapped after an earthquake.
Further information: A Swarm-Intelligence Approach to Oil Spill Mapping using Unmanned Aerial Vehicles (arc.aiaa.org/doi/10.2514/6.2017-1157)