What does it take for an autonomous robot to be faster around a course than human drone pilots? At these dizzying speeds, humans need lightning-fast reflexes. Researchers at Delft University of Technology (the Netherlands) have developed an AI system that enables a racing drone to navigate demanding courses at extreme speed using only a single camera. It outperformed even former world champion human drone pilots in a race.
Now published in Science Robotics, the scientific work behind this accomplishment shows how compact, efficient neural-network-based control can achieve high-performance autonomous flight under real-world conditions. The underlying principles could help advance a much broader class of autonomous robots, from vehicles to mobile and humanoid systems.
The TU Delft team set out to investigate how far artificial intelligence can push a drone with very limited sensors, onboard computing power and energy. This is a challenging problem: at high speed, even a small delay in sensing or control can mean missing a gate, colliding with an obstacle or losing control and crashing.
The result is MonoRace, an autonomous flight system developed at the MAVLab of TU Delft's Faculty of Aerospace Engineering. Unlike previous leading autonomous racing systems, MonoRace uses just one forward-facing camera and an inertial measurement unit (IMU) for perception, navigation and control.
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