Autonomous Drones Learn Challenging Acrobatics
Researchers at the University of Zurich have developed a navigation algorithm that enables drones to learn acrobatic maneuvers using nothing more than onboard sensor measurements. Autonomous quadcopters can be trained using simulations to increase their speed, agility, and efficiency — capabilities that have applications in search and rescue operations. The researchers demonstrated maneuvers like a power loop, a barrel roll, and a matty flip. The key to the algorithm is an artificial neural network that combines input from the onboard camera and sensors and translates this information into control commands. The neural network is trained solely through simulated acrobatic maneuvers.