| Developers: | Moscow Institute of Physics and Technology (MIPT) |
| Date of the premiere of the system: | 2025/12/19 |
| Branches: | Electrical and Microelectronics |
| Technology: | UAV - Unmanned aerial vehicle, Robotics |
The main articles are:
2025: Development of Robot Bird Wing Control System
Scientists MIPT have developed a bird wing control system robot that simulates the work of the nerve centers of living things. It is designed for drones a new generation that can use energy and maneuver in hard-to-reach places: forests, caves, inside destroyed buildings or dense urban buildings. The university announced this on December 19, 2025.
Birds loop easily between tree crowns, quickly restore flight mechanics during collisions and save energy by using air flows for planning. Honed by millions of years of evolution, they surpass any screw drones.
To create the same perfect robots, it is not enough to simply attach wings to them, you need to reproduce the flight control system itself, which in birds is based on the work of the nervous system.
This problem is solved in the laboratory of neurobiomorphic technologies of MIPT. Scientists have already created a prototype of a zoomorphic flying drone - an ornithopter. And now they have developed a system for controlling its wings. It literally copies the central generator of animal patterns (CGP) - the work of neural structures in the spinal cord responsible for rhythmic movements. Its peculiarity is in synchronicity: neurons that control the muscles for lowering and raising the wing work in a strict order, creating rhythmic "bursts" of activity.
Scientists have created a simplified version of such a system using a mathematical model of a pulsed neuron. She describes the behavior of real nerve cells, their ability to generate "discharges" and "fade." Between the neural network that simulates CPF and the engine on the wings, scientists have introduced an important link - the muscle model. The relationship between them was described using a system of differential equations. Their parameters determine how quickly and strongly the "muscle" responds to a nerve impulse.
The neural system does not simply provide for the movement of the robot. This is a dynamic self-regulating system that, without external commands, is able to maintain rhythm and synchronize waves. Thanks to internal connections, it is resistant to external interference and quickly returns to stable operation.
Two independent robot servomotors convert the complex "neural" signals of the network into accurate wing kinematics and reproduce the natural trajectory for the bird with accelerations, pauses and microcorrections.
The architecture is ready to connect feedback sensors, which will allow the robot bird to independently stabilize flight in turbulence, parry wind gusts and recover from collisions.
Such opportunities pave the way for the creation of drones of a new class. They will be able to operate where conventional screw drones are helpless: in dense forests to monitor ecosystems, inside warehouse complexes and destroyed buildings for search and rescue operations.
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