Researchers from the Moscow Institute of Physics and Technology and the Skoltech Institute have developed a new algorithm to enhance the stability of miniature drones equipped with flapping wings.
The researchers drew inspiration for the drones' operating principle from bumblebees, enabling the robot to maintain its balance even in strong winds. These robots could be used for debris removal during emergencies, targeted pollination of plants in enclosed farms, and surveillance tasks.
Tests of the digital model showed that the new algorithm has a high degree of stability.
Nikolay Ivanov, associate professor in the Department of Computer Science and Computational Mathematics and head of the research team, noted that the next step is to develop a working prototype.
He said: “If the relevant authorities show interest, we will be able to manufacture a prototype of a small drone within a period ranging from six months to several years. There is currently a similar prototype developed by Chinese manufacturers, but it does not have sufficient stability during flight. There are also no ready-made solutions or components for this type of aircraft. The biggest obstacle is the power source, because current batteries are relatively heavy, and perhaps the solution is to use an external power source via a wire.”
Bumblebees are among the most maneuverable insects, capable of hovering in place, rotating in extremely tight spaces, flipping over, and changing direction very quickly. This is due to their vortex aerodynamics, where each wing flap generates air vortices that provide the lift necessary for flight.
Flapped flight is inherently unstable, but a bee's nervous system processes information in real time from its eyes, antennae, and balance system, constantly adjusting wing movements to maintain stability. When this technique is mimicked in robots, they lose balance even in a light breeze.
The researchers were able to develop a new algorithm for stabilizing small flapping-winged flying robots, along with a computer simulation environment that allows testing of different control systems in turbulent airflow conditions.
