Smooth landing of multi-rotor drones is difficult due to the complex aerodynamic effects caused by interactions between multi-rotor airflow and the environment.
Complex turbulence is created by the airflow from each rotor bouncing off the ground as the ground grows ever closer during a descent.
This turbulence is not well understood particularly for autonomous drones. That is why takeoff and landing are often the two trickiest parts of a drone flight.
Now, researchers from California Institute of Technology (Caltech) have developed an Artificial Intelligence (AI)-based system that can help drones to land more safely and quickly, while gobbling up less power.
They named their AI system as ‘Neural Lander’. It is a learning-based controller that tracks the position and speed of the drone, and modifies its landing trajectory and rotor speed accordingly to achieve the smoothest possible landing.
It has the potential to help drones fly more smoothly and safely, especially in the presence of unpredictable wind gusts, and eat up less battery power as drones can land more quickly
