The Abu Dhabi Autonomous Racing League (A2RL), part of the Advanced Technology Research Council (ATRC), in collaboration with the Drone Champions League (DCL), concluded the inaugural A2RL x DCL Autonomous Drone Championship in the Middle East, at Marina Hall, ADNEC Centre Abu Dhabi.
Team MAVLab’s AI drone outpaced a world-leading human pilot to win the AI vs Human Challenge. The head-to-head duel was the most complex ever staged, featuring finalists from the DCL Falcon Cup—some of the top drone pilots in the world.
Over 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.
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. 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 course design pushed the boundaries of perception-based autonomy—featuring wide gate spacing, irregular lighting, and minimal visual markers. The use of rolling shutter cameras 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 championship highlights included MAVLab (TU Delft) winning the AI Grand Challenge, setting the fastest time on the 170m course, completing two laps (22 gates) in just 17 seconds. MAVLab also won the AI vs Human Showdown with its autonomous drone outpacing a human pilot.
TII Racing emerged victorious in the multi-drone format, in a high-speed test of AI coordination and collision avoidance. MAVLab (TU Delft) claimed victory in the world’s first AI-only drag race, demonstrating straight-line speed and control under high acceleration against the championship’s top teams.
His Excellency Faisal Al Bannai, Adviser to the UAE President for Strategic Research and Advanced Technology Affairs, and Secretary-General of ATRC, said: “At ATRC, we believe innovation must be proven in the real world, not just promised. 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.”
Stephane Timpano, CEO of ASPIRE, the hosting entity of the Abu Dhabi Autonomous Racing League, said: “The future of flight doesn’t live in a lab – it lives on the racetrack. What we saw this weekend brings us closer to scaling autonomous systems in everyday life.”
Markus Stampfer, Executive Chairman of DCL, said: “We brought elite racing conditions to autonomous flight—and the AI rose to the challenge. This was a major leap for both sport and technology.”
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."
The A2RL X DCL Drone STEM Program, designed in collaboration with UNICEF and under the supervision of the ATRC, has trained more than 100 Emirati students this year. Over 60 per cent earned the prestigious Trusted Operator Program certification and 24 achieved perfect scores, showcasing the cutting-edge aviation skills being developed as part of the program.
With the drone finale now in the books, all eyes turn to Season 2 of A2RL’s autonomous car racing series, set for Q4 2025 at Yas Marina Circuit in Abu Dhabi.
