Owl-inspired drones aim for agility in cities and efficiency at sea

Researchers at the University of Surrey are developing owl-inspired fixed-wing drones that combine the endurance of traditional fixed-wing designs with the agility of rotary-wing drones. Their project, called ‘Learning2Fly,’ studies how birds of prey like owls navigate complex environments to enable drones to perch, pivot, and maneuver precisely through cluttered urban airspace or turbulent offshore wind conditions. By integrating experimental flight data with machine learning, the team aims to create drones that can predict and control their motion in real time, overcoming limitations of conventional aerodynamic simulations. The research involves real-world testing of lightweight drone prototypes in Surrey’s motion capture lab, where onboard sensors and high-speed cameras track three-dimensional flight behavior. This data trains machine learning models to anticipate drone responses to sudden air shifts and obstacles, improving reliability in unpredictable environments. Early results are promising, showing improved drone performance in complex conditions. The next phase will involve outdoor trials to validate adaptability to wind turbulence and moving obstacles, potentially enabling a new generation of drones capable of efficient,