In partnership with Intel, a team of researchers from the University of Zurich has enabled autonomous drones to fly complicated maneuvers using only onboard sensors and AI.
Autonomous drones fly complicated maneuvers using onboard sensors and AI
Researchers from the University of Zurich, Zwitserland have developed an algorithm that enables drones to autonomously fly very technical maneuvers in both indoor and outdoor spaces.
During the flight, the unmanned aircraft only rely on onboard sensor measurements and artificial intelligence to avoid crashing. In a demonstration, the researchers showed the drones performing complicated maneuvers, such as a Power Loop, Barrel Roll, and a Matty Flip.
“This navigation is another step towards integrating autonomous drones in our daily lives,” says Davide Scaramuzza, robotics professor and head of the robotics and perception group at the University of Zurich, reports Futurity.
An artificial neural network lies at the core of the new algorithm as is explained in this paper. It combines input from the onboard camera and sensors, which then translates into new control commands. The algorithm is purely trained through simulated accurate acrobatic maneuvers. The benefit of training the algorithm this way is that you avoid expensive demonstrations by human pilots. And, since the training happens in a virtual environment, there’s no risk of damaging the quadcopter.
The autonomous drone are ready for real flight after only a few hours of simulated training exercises. However, as of now, human pilots are still better than autonomous drones using an artificial intelligence system.
“Human pilots can quickly process unexpected situations and changes in the surroundings, and are faster to adjust,” says Scaramuzza.
However, the team of researchers is convinced that drones that are used for search and rescue missions, or delivery services will benefit from artificial intelligence to cover long distances quickly and efficiently.
You can read more about how drones are being used for research here.
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Photos: Elia Kaufmann