Funded by: Afeyan Family Foundation
PI: Habet Madoyan
As autonomous systems become increasingly central to global technological innovation, Armenia has an opportunity to lead in specialized areas like unmanned aerial vehicle (UAV) control. The project proposed the development of an intelligent, reinforcement learning (RL)-based system for real-time adjustment of PID (proportional-integral-derivative) coefficients-crucial for stable and responsive UAV flight.
Traditional PID tuning methods are manual, time-consuming and require domain expertise. The proposed approach aimed to leverage cutting-edge machine learning to automate this process, enabling UAVs to dynamically adapt to changing flight conditions such as wind, payload, or mission type. The outcome would be a fully functional, open-source module integrated into UAV firmware, with improved flight performance demonstrated in both simulated and real-world environments.
The project was led by Habet Madoyan (PI), in collaboration with Davit Ghazaryan of AUA and Aram Harutyunyan from Airworker, one of Armenia’s leading UAV manufacturers. This academic-industry partnership ensureed both research rigor and direct impact on Armenia’s growing UAV sector. Importantly, the initiative also provided AUA students with applied research experience at the intersection of artificial intelligence, robotics and control systems.
