Unlike birds that effortlessly navigate through dense forests and complex environments, traditional drones have typically relied on external guidance systems or pre-mapped routes. However, a revolutionary development from Professor Fu Zhang and researchers at the University of Hong Kong has dramatically changed this paradigm.
Their creation, aptly named SUPER (Safety-Assured High-Speed Aerial Robot), emulates avian flight capabilities more closely than any previous technology. This compact drone—with a wheelbase of just 280mm and weighing only 1.5kg—can reach speeds of over 20 meters per second (45 mph) while autonomously avoiding obstacles as thin as power lines or twigs.
The breakthrough lies in SUPER's sophisticated integration of hardware and software. The system utilizes a lightweight 3D LiDAR sensor capable of detecting obstacles up to 70 meters away with pinpoint accuracy. This is paired with an advanced planning framework that generates two trajectories during flight: one optimizing speed by venturing into unknown spaces and another prioritizing safety by remaining within known, obstacle-free zones.
"It's like giving the drone the reflexes of a bird, enabling it to dodge obstacles in real-time while racing toward its goal," explains Professor Zhang. The system allows micro air vehicles (MAVs) to navigate complex environments with unprecedented safety and efficiency, even in challenging conditions like dense forests at night.
The implications for various industries are substantial. In search and rescue operations, drones equipped with this technology could swiftly navigate disaster zones like collapsed buildings or dense forests, locating survivors and assessing hazards more efficiently than current systems. Other applications include autonomous delivery, power line inspection, environmental monitoring, and mapping of inaccessible areas.
As the global drone market is projected to reach $163.60 billion by 2030, with the autonomous segment growing at over 17% annually, innovations like SUPER are positioned to transform how drones operate in real-world scenarios. The research has been published in Science Robotics, marking a significant milestone in transitioning high-speed autonomous navigation from laboratory settings to practical applications.