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Learning-Based Controller Uses AI to Land Multi-Rotor Drones

Landing multi-rotor drones smoothly is difficult. Complex turbulence is created by the airflow from each rotor bouncing off the ground as the ground grows closer during descent. Drones typically wobble and inch slowly toward a landing until power is finally cut and they drop the remaining distance to the ground.

Caltech artificial intelligence experts developed the Neural Lander, a learning-based controller that helps drones fly more smoothly and safely, especially in the presence of unpredictable wind gusts. It also helps reduce battery power since drones can land more quickly.

Source 

Topics:
Aeronautics Aerospace

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