Drones controlled by Artificial Intelligence can already deliver similar performance today to those controlled by humans. Even in an urban setting they are capable of navigating safely.
Congested streets, rising emission levels and the lack of parking all combine to make urban logistics an increasingly greater challenge. Powered by e-commerce, the package market is growing by seven to ten per cent annually in mature markets such as the United States or -Germany. This will see the volume double in Germany by 2025, with around five billion packages mailed each year. “While -deliveries to consumers have previously made up about 40 per cent, more than half of all packages are now delivered to private households. Timely delivery in ever greater -demand,” says Jürgen Schröder, a McKinsey -Senior Partner and expert in logistics and postal services. “New technologies like autonomous driving and drone delivery still need to be developed further. They present opportunities to reduce costs and simplify delivery. We expect that by 2025, it will be possible to deliver around 80 per cent of packages by automated means.”
Package-carrying drones, as Amazon put forward for the first time in 2013, were initially laughed off as a crazy idea. Today, a large number of companies are experimenting with delivery by drone. One example is Mercedes-Benz with its Vans & Drones concept, in which the package is not directly delivered to the customer via a drone, but in a commercial vehicle. In the summer of 2017, the company carried out autonomous drone missions for the first time in an urban environment in Zurich. In the course of the pilot project, -customers could order selected products on Swiss online marketplace siroop. These were a -maximum of two -kilograms in weight and suitable for transport by drone. The range of products included coffee and -electronics. The -customers received their goods the same day. The retailer loaded the drones immediately after receiving the -order on its own premises. After this, they flew to one of two Mercedes vans used in the project, which featured an -integrated drone landing platform. The vans stopped at one of four -pre–determined “rendezvous points” in the Zurich metropolitan area. At these points, the mail carriers received the products and delivered them to the customers, while the drone returned to the retailer. Overall, some 100 flights were -successfully completed without any incidents across the urban area. “We believe that drone-based logistics networks will fundamentally change the way we access products on a daily basis,” says Andreas Raptopoulos, Founder and CEO of Matternet, the manufacturer of the drones used in the test.
Reliably dodging obstacles thanks to Artificial Intelligence
An essential element of such applications are drones that can fly safely between buildings or in a dense street network, where cyclists and pedestrians can suddenly cross their path. Researchers at the University of Zurich and the NCCR Robotics research centre developed an intelligent solution for this purpose. Instead of relying on sophisticated -sensor systems, the drone developed by the Swiss -researchers uses a standard smartphone camera and a very -powerful AI -algorithm called DroNet. “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,” explains Davide Scaramuzza, Professor for Robotics and Perception at the University of Zurich. For each input image, the algorithm generates two outputs: one for navigation to fly around obstacles and one for the likelihood of collisions to detect dangerous situations and make it possible to respond. In order to gain enough data to train the algorithm, information was collected from cars and bicycles that were travelling in urban environments in accordance with the traffic rules. By imitating them, the drone -automatically learned to respect the safety rules, for example “How do we follow the street without crossing into the oncoming lane” or “How do we stop when obstacles like pedestrians, construction works or other vehicles block the way?”. Having been trained in this way, the drone is not only capable of navigating roads, but also of finding its way around in completely different environments than those it was ever trained for – such as multi-storey car parks or office corridors.
Drones controlled by Artificial Intelligence are winning the race
Just how sophisticated drones controlled by Artificial Intelli-gence are today was demonstrated in a race organised by NASA’s Jet Propulsion Laboratory (JPL), when world-class drone pilot Ken Loo took on Artificial Intelligence in a timed trial. “We pitted our algorithms against a human, who flies a lot more by feel,” said Rob Reid of JPL, the project’s task manager. Compared to Loo, the drones flew more cautiously but consistently. The drones needed around 3 seconds longer for the course, but kept their lap times constant at a speed of up to 64 kilometres per hour, while the human pilot varied greatly and was already exhausted after a few laps.