Swiss researchers develop AI autonomous urban drone navigation system

Researchers of the University of Zurich and the National Centre of Competence in Research NCCR Robotics have developed an algorithm that can safely drive a drone through the streets of a city. Instead of relying on sophisticated sensors, the drone and DroNet navigation system developed by Swiss researchers uses a standard smartphone camera and a very powerful artificial intelligence algorithm (AI) to interpret the scene it observes and react accordingly. The algorithm consists of a so-called Deep Neural Network. “This is a computer algorithm that learns to solve complex tasks from a set of ‘training examples’ that show the drone how to do certain things and cope with some difficult situations, much like children learn from their parents or teachers”, says Davide Scaramuzza, Professor for Robotics and Perception at the University of Zurich.

The algorithm produces two outputs for each single input image: a steering angle to keep the drone navigating while avoiding obstacles, and a collision probability to let the drone recognise dangerous situations and promptly react to them. “DroNet recognises static and dynamic obstacles and can slow down to avoid crashing into them. With this algorithm we have taken a step forward towards integrating autonomously navigating drones into our everyday life”, says says Davide Scaramuzza.

One of the most difficult challenges in Deep Learning is to collect several thousand ‘training examples’, according to an NCCR press release. “To gain enough data to train their algorithms, Prof. Scaramuzza and his team collected data from cars and bicycles that were driving in urban environments. By imitating them, the drone automatically learned to respect the safety rules, such as “How do we follow the street without crossing into the oncoming lane?”, and “How do we stop when obstacles like pedestrians, construction works, or other vehicles, block the way?” Even more interestingly, the researchers showed that their drones learned to not only navigate through city streets, but also in completely different environments, where they were never taught to do so. Indeed, the drones learned to fly autonomously in indoor environments, such as parking lots and office’s corridors.”

According to NCCR this research opens potential for monitoring and surveillance or parcel delivery in cluttered city streets as well as rescue operations in disastered urban areas. Nevertheless, the research team warns from exaggerated expectations of what lightweight, cheap drones can do. “Many technological issues must still be overcome before the most ambitious applications can become reality,” says PhD Student Antonio Loquercio.

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