AI-enabled control system helps autonomous drones stay on target in uncertain environments

MIT researchers developed a machine learning-based adaptive control algorithm for autonomous drones facing unpredictable forces like gusty winds. The system uses meta-learning to automatically choose optimization algorithms and learn from minimal flight data, reducing trajectory errors by 50% compared to baselines in simulations. This adaptive control could help drones deliver packages or monitor fire-prone areas more efficiently despite strong winds, potentially improving performance in challenging real-world conditions.