We’re excited to watch DRL and drone racing continue to grow, as the league and sport reach new and larger audiences. Daniel Cohen, a senior vice president with Octagon’s Global Media Rights Consulting group, concludes:ĭRL is one of the most exciting new properties in sports and offers sports media platforms thrilling content. Horbaczewski’s thoughts are echoed by the firm that helped DRL secure international media rights deals. We’ve got an incredible team, the most tech-savvy fans of any sports league in the world, and a massive global distribution network from the US to China that has doubled our reach and fanbase. Over the past year, we’ve dramatically scaled our sport through A-list talent recruitment, in-depth fan research, and innovative partnerships with top global brands and media platforms. These “tech-setters,” the league says, love social media equally and are responsible for fueling DRL’s massive 400% growth on TikTok in the past year.Īlso read: DJI updates Fly app, Mavic Air 2 drone firmwareĭRL CEO/founder Nicholas Horbaczewski is positive that drone racing will soon find a place among other major sporting leagues on the wings of new international broadcast agreements, new global partnerships, and new ways for fans to engage with the sport. So much so, DRL has emerged as the most followed drone brand on Weibo in China – a country where the league has tripled its viewership over the last year.ĭRL credits its growth to young, global, tech-savvy fans who do not follow traditional sports or e-sports, but love tech-powered sports like drone racing.

Streaming platforms such as Twitter, Star+, Weibo, and Yhizibo also helped to increase the league’s global awareness. The professional drone racing property says its 2021-22 events were broadcast on six continents through partnerships with more than a dozen sports networks. At the same time, digital viewership of DRL races has also skyrocketed, interestingly revealing China as the league’s second-largest market behind the United States. Photo credit: Dylan Buell/Drone Racing League for Getty Imagesĭrone Racing League (DRL) says it has more than doubled its broadcast reach with the just-concluded 2021-22 season of high-speed drone racing. 16, 2022 /PRNewswire/ - The Drone Racing League (DRL), the worlds premier professional drone racing property, announced expanded global media distribution for 2022-23 DRL Algorand. Other information related to this project was presented at the IEEE International Conference on Robotics and Automation in London this year – see User-Conditioned Neural Control Policies for Mobile Robotics, or here.Thousands of fans attended DRL's 2021-22 Championship event in Las Vegas. The AI is described in detail in the Nature paper ‘ Champion-level drone racing using deep reinforcement learning‘, which can be read in full without payment.Īccording to this paper, Swift consists of two modules: a perception system that translates high-dimensional visual and inertial information into a low-dimensional representation, then a control policy that takes that representation and issues control commands – the latter is the deep reinforcement trained feed-forward neural network. “On the other hand,” said the University, “human pilots proved more adaptable than the autonomous drone, which failed when the conditions were different from what it was trained for – for example if there was too much light in the room.” It had the fastest lap, with Vanover half a second behind with the fastest human lap. Swift lost some, but won more against each of the humans. In each race, two drones flew simultaneously, one controlled by a human and one by the AI.

Marvin Schaepper – thrice Swiss national champion.

Thomas Bitmatta – twice MultiGP international open world cup champion.

Alex Vanover – 2019 Drone Racing League world champion.

The humans had a week to practice on the track, and were: The races – held in 2022 – were on a 75m long track designed by a professional drone racer, said the University, defined by seven square gates through which the drones had to pass, all inside a 30 x 30 x 8m volume. “To make sure that the consequences of actions in the simulator were as close as possible to the ones in the real world, we designed a method to optimise the simulator with real data,” said Zurich researcher Elia Kaufmann.įurther training involved flying a real drone automatically, and feeding back into the learning process the on-board camera and IMU data, plus extra information gathered from an external position-tracking system – a tracking system that was not used during the races. “The use of simulation helped avoid destroying multiple drones in the early stages of learning.” “Swift was trained in a simulated environment where it taught itself to fly by trial and error, using ‘ reinforcement’ learning,” according to the university.

Drone racing league 2022