AI Quadcopter 'Swift' Beats Top Human Drone Racers

An autonomous, artificial-intelligence-powered drone called Swift has beaten humanity's best drone racers. "The AI-equipped drone, developed by researchers at the University of Zurich, came out on top in 15 out of 25 races and recorded the single fastest lap time," reports Gizmodo. The findings have been published in the journal Nature. From the report: Swift beat the humans in the niche but growing sport of first-person view drone racing. Human competitors navigate using a headset connected to a camera on their drones to pilot a quadcopter through complex obstacle courses at extreme speeds, with the goal of finishing the race with the fastest time and avoiding taking too much damage in the process. Drones in these races can top 50 miles per hour when they're really buzzing. The [video here] shows Swift battling it out against the human-controlled drones. Swift emerged victorious in 15 out of the 25 total head-to-head races against the human pilots and clocked the fastest overall lap time at 17.47 seconds. That brisk lap time was nearly half a second better than the best human. The three human competitors, Alex Vanover, Thomas Bitmatta, and Marvin Schaepper, have each won drone racing championships in the past. In this case, the human competitors had a week to learn the new course and train for the race. During that same time, Swift was training as well but in a digitally simulated environment meant to resemble the course. Swift, according to the paper, used deep reinforcement learning while in the simulation along with additional data collected from the outside world. During the actual race, Swift would take in video collected by its camera and send that to a neural network capable of identifying the gates it had to fly through. A combination of onboard sensors are then used to aid the drone with positioning, speed, and orientation. All of this happened autonomously, at extreme speeds. The researchers noticed some interesting differences in the ways Swift approached the course as opposed to its human competitors. The autonomous system, they noted, was more consistent across laps and appeared to take tighter turns. Those tight turns can add up and give a drone an edge in a race by repeatedly shaving off fractions of a second from lap times.

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