Latest news with #ChristopheDeWagter
Daily Tribune
18-04-2025
- Automotive
- Daily Tribune
AI Drone Defeats Human Pilots in $1M Abu Dhabi Racing League Showdown
In a groundbreaking moment for artificial intelligence and robotics, an AI-powered drone has defeated elite human pilots at the Abu Dhabi Autonomous Racing League (A2RL), marking a new era in autonomous flight. Hosted at ADNEC Marina Hall in collaboration with the Drone Champions League (DCL), the event showcased the world's most advanced autonomous aerial racing technology. A total of 14 teams from countries including the UAE, Netherlands, Austria, South Korea, China, and the US competed across multiple challenges for a $1 million prize pool. 🔸 Dutch Innovation Soars The standout performer of the tournament was MavLab from Delft University of Technology, Netherlands, which claimed victory in three out of four categories. Most notably, the team's AI-powered drone completed two laps of a 170-metre course in just 17 seconds, winning the AI Grand Challenge. In a historic AI vs. Human showdown, MavLab's drone edged out three champion human pilots from DCL in head-to-head races. This marked the first time an autonomous system has decisively outperformed professional human pilots in competitive drone racing. 'Winning three top titles is a huge milestone for our team,' said Christophe De Wagter, team principal at MavLab. 'I always wondered when AI would be able to compete with human drone racing pilots in real competitions. I'm extremely proud that we've made it happen this year.' 🔸 UAE's TII Claims a Victory of Its Own The Technology Innovation Institute (TII) of Abu Dhabi also left a strong mark by winning the multi-autonomous drone AI race, which tested coordination, real-time navigation, and collision avoidance. TII's win highlighted the region's growing influence in advanced AI and robotics research. 🔸 A Test of Pure Autonomy Each team raced standardised drones with zero human input — guided solely by onboard AI algorithms. These drones, equipped with a compact computing module, a forward-facing camera, and an inertial measurement unit, navigated a complex course at speeds exceeding 150 km/h. Challenging lighting, sparse visual markers, and the use of rolling shutter cameras further pushed the limits of real-time AI performance, making this the most demanding autonomous drone race ever held globally. 🔸 What's Next? This competition, part of a broader initiative by Abu Dhabi's Advanced Technology Research Council (ATRC), not only set a new benchmark in AI racing but also demonstrated the growing capabilities of autonomous systems in real-world conditions. As AI continues to evolve, such achievements underscore its ability to outperform humans in fields once thought impossible — and drone racing may just be the beginning.
Gulf News
18-04-2025
- Science
- Gulf News
Watch: AI drone beats human pilot in Abu Dhabi's $1 million prize pool autonomous race
Abu Dhabi: AI is no longer learning from humans – it's starting to beat them. In a major breakthrough for autonomous flight and aerial robotics, an AI-powered drone has outpaced human pilots in a global competition held in Abu Dhabi. The Abu Dhabi Autonomous Racing League (A2RL), a project under the Advanced Technology Research Council (ATRC), in collaboration with the Drone Champions League (DCL), hosted one of the world's most sophisticated drone races at ADNEC Marina Hall. A total of 14 international teams made it to the finals week, competing for a $1 million prize pool. Teams from the UAE, Netherlands, Austria, South Korea, the Czech Republic, Mexico, Turkey, China, Spain, Canada, and the US represented university labs, research institutes, and deep-tech startups. The highlight? MavLab, from the Delft University of Technology in the Netherlands, secured victories in three out of four competitions. They clinched the AI Grand Challenge with their drone completing two laps of the 170-metre course in just 17 seconds. MavLab won the world's first AI-only drag race, demonstrating straight-line speed and precision under intense acceleration. In a landmark moment, MavLab's autonomous drone defeated three top DCL champion pilots in a head-to-head AI-versus-human showdown. With precision flying, the AI-powered drone edged out its human-piloted rivals in thrilling contests. (Watch the video) 'Winning three top titles is a huge milestone for our team,' said Christophe De Wagter, team principal of MavLab. 'I always wondered when AI would be able to compete with human drone racing pilots in real competitions. I'm extremely proud of the team that we were able to make it happen already this year.' The results, he underlined, validates years of research and experimentation in autonomous flight. 'To see our algorithms outperform in such a high-pressure environment and take home the largest share of the prize pool, is incredibly rewarding,' De Wagter noted. Meanwhile, Technology Innovation Institute (TII), Abu Dhabi, bagged the multi- autonomous drone AI race in a high-speed challenge that tested coordination, navigation, and collision avoidance between multiple autonomous units. How did they race? Each team raced a standardised drone equipped with a compact computing module, a forward-facing camera and an inertial measurement unit. With zero human input, the drones relied solely on real-time processing and AI-driven decision-making, hitting speeds of more than 150 km/h through a challenging course. The race environment pushed the boundaries of perception-based autonomy, with wide gate spacing, irregular lighting, and minimal visual markers. To raise the difficulty, the event used rolling shutter cameras – further testing each team's ability to achieve fast, stable performance in visually sparse conditions. This was the first time an autonomous drone race of this scale and complexity was held under such constraints, underscoring the technical sophistication of the event.
Khaleej Times
17-04-2025
- Science
- Khaleej Times
Watch: Human pilot, AI race their drones in Abu Dhabi; who won?
A drone piloted by AI has convincingly beaten a human-controlled machine in an international drone racing competition in Abu Dhabi, marking a significant milestone in the development of artificial intelligence and autonomous flight. It also marked a global first, where AI outpaced human pilots 'in a race of such scale, speed and complexity featuring some of the top drone pilots in the world,' organisers of the inaugural A2RL (Abu Dhabi Autonomous Racing League) x DCL (Drone Champions League) Autonomous Drone Championship said on Wednesday. The AI-piloted drone of Team MavLab from Delft University of Technology (TU Delft), The Netherlands) outdone a world-leading human pilot to win the AI vs Human Challenge, one of the four race formats. Team Mavlab also dominated two other races, including the AI Grand Challenge, where it set the fastest time on the 170-meter course by completing two laps (22 gates) in just 17 seconds. The same team from TU Delft also claimed top spot in the Autonomous Drag Race, touted as the world's first AI-only drag race. Team Mavlab demonstrated straight-line speed and control under high acceleration against other top teams. Meanwhile, TII Racing (Technology Innovation Institute, Abu Dhabi) won the AI Multi-Autonomous Drone Race, a high-speed test of AI coordination and collision avoidance. The goal of the competition was to push the frontier of AI. The drone had access to just one forward-looking camera, a major difference from previous autonomous drone races. This is more similar to how human first-person view (FPV) pilots fly, and leads to additional perception challenges for the AI. Head-to-head duel The head-to-head duel between AI and humans was the most complex ever staged. 'With no human input, the drones relied entirely on real-time processing and AI-driven decision-making to reach speeds exceeding 150 km/h through a complex race environment,' the organisers noted. Watch the video below: The course design pushed the boundaries of perception-based autonomy— featuring wide gate spacing, irregular lighting, and minimal visual markers. Each team raced a standardised drone equipped with the compact yet powerful Nvidia Jetson Orin NX computing module, a forward-facing camera, and an inertial measurement unit (IMU) for onboard perception and control. The use of rolling shutter cameras (a type of image capture in cameras that records the frame line by line instead of capturing the entire frame all at once) further heightened the difficulty, testing each team's ability to deliver fast, stable performance under demanding conditions. 'This marked the first time an autonomous drone race of this scale and complexity was staged on such a visually sparse track, underscoring the ambition and technical challenge of the event,' the organisers added. Christophe De Wagter, team principal of MavLab, said: 'Winning the AI Grand Challenge and the AI vs Human race is a huge milestone for our team. It validates years of research and experimentation in autonomous flight. To see our algorithms outperform in such a high-pressure environment and take home the largest share of the prize pool, is incredibly rewarding." For two days, 14 international teams qualified for the finals week, with the top four advancing to compete across multiple challenging race formats. Teams from the UAE, Netherlands, Austria, South Korea, the Czech Republic, Mexico, Turkey, China, Spain, Canada and the USA represented a mix of university labs, research institutes, and startup innovators, and battled it out for the $1million prize pool across four race formats. How AI won? The team of scientists and students from TU Delft won the competition by developing an efficient and robust AI system, capable of split-second, high-performance control. They noted: 'Whereas earlier breakthroughs, like AI defeating world champions at chess or Go, have taken place in virtual settings, this achievement happened in the real world. Two years ago, the Robotics and Perception Group at the University of Zürich was the first to beat human drone racing champions with an autonomous drone. However, that impressive achievement occurred in a flight lab environment, where conditions, hardware, and the track were still controlled by the researchers – a very different situation from this world championship, where the hardware and track were fully designed and managed by the competition organisers.' Team Mavlab created one of the core new elements of the drone's AI that did not require to send control commands to a traditional human controller, but directly to the motors. The deep neural networks were able to mimick the outcomes of traditional algorithms with less processing time. Real-life applications 'The highly efficient AI developed for robust perception and optimal control are not only vital to autonomous racing drones but will extend to other robots,' noted Wagter, explaining: 'Robot AI is limited by the required computational and energy resources. Autonomous drone racing is an ideal test case for developing and demonstrating highly-efficient, robust AI.' Speed is a very important element since drones have a very limited battery capacity. This means, the faster they fly, the more distance they can cover. 'Flying drones faster will be important for many economic and societal applications, ranging from delivering blood samples and defibrillators in time to finding people in natural disaster scenarios. Moreover, we can use the developed methods to strive not for optimal time but for other criteria such as optimal energy or safety. This will have an impact on many other applications, from vacuum robots to self-driving cars,' Wagter added. Meanwhile, the A2RL X DCL Drone STEM Program, designed in collaboration with Unicef and under the supervision of Advanced Technology Research Council (ATRC), has trained more than 100 Emirati students this year. 'At ATRC, we believe innovation must be proven in the real world, not just promised,' said Faisal Al Bannai, adviser to the UAE President for Strategic Research and Advanced Technology Affairs, and secretary-general of ATRC. He underscored 'A2RL is more than a race, it's a global testbed for high-performance autonomy and reflects the UAE's commitment to advancing AI, robotics, and next-gen mobility responsibly.'
