Hi... You are watching in-depth with ILA. In a stunning development, an AI drone pilot has decimated the best of human drone pilots in a competition. Three world champion drone pilots were recently defeated in a competition by an autonomous, artificial-intelligence-powered drone. This is the first time that a drone powered by AI has beaten a human champion in a real physical sport designed for, and by, humans. 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 at 17.47 seconds. That brisk lap time was nearly half a second better than the best of human drone pilots. The three human competitors, Alex Vanover, Thomas Bitmatta, and Marvin Schaepper, have each won drone racing championships in the past. All three expert drone racers were beaten by an algorithm that learned to fly a drone around a 3D racecourse at breakneck speeds without crashing.
#SwiftAIdrone #AIdronebeatshumans #FPVdroneracing
~HT.99~PR.153~
#SwiftAIdrone #AIdronebeatshumans #FPVdroneracing
~HT.99~PR.153~
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00:00 Hi, you are watching InDepth with Elo.
00:09 In a stunning development, an AI drone pilot has decimated the best of human drone pilots
00:15 in a competition.
00:17 Three world champion drone pilots were recently defeated in a competition by an autonomous,
00:22 artificial intelligence-powered drone.
00:25 This is the first time that a drone powered by AI has beaten a human champion in a real
00:31 physical sport designed for, and by, humans.
00:34 The AI-equipped drone, developed by researchers at the University of Zurich, came out on top
00:41 in 15 out of 25 races and recorded the single fastest lap time at 17.47 seconds.
00:49 That brisk lap time was nearly half a second better than the best of human drone pilots.
00:55 The three human competitors, Alex Vanover, Thomas Bitmata, and Marvin Schieper, have
01:01 each won drone racing championships in the past.
01:04 All three expert drone racers were beaten by an algorithm that learned to fly a drone
01:10 around a 3D race course at breakneck speeds without crashing.
01:15 The name of this artificial intelligence-powered drone is Swift, and the competition in which
01:20 it prevailed was the FPV drone racing.
01:24 Swift has been created jointly by the researchers at the University of Zurich and Intel.
01:30 FPV drone racing is a thrilling sport where competitors control high-speed drones through
01:36 complex obstacle courses.
01:39 Pilots, wearing headsets, remotely control the drones while viewing a live video feed
01:44 from the drone's onboard camera, offering an immersive first-person perspective.
01:50 This race involves humans piloting small quadcopters around a course with a speed of over 100 km/h
01:57 with the vehicles being subjected to g-forces of up to 5G.
02:01 Swift Drone combines machine vision with real-time data capture through an onboard camera, mirroring
02:07 the setups human racers use.
02:10 Adding to its suite of features, Swift boasts an integrated inertial measurement unit gauging
02:15 the drone's speed and acceleration.
02:18 All this information feeds into an artificial neural network that computes the drone's location
02:24 in real-time and discerns race gates.
02:27 Furthermore, a deep neural network-based control unit determines the optimal racing path, ensuring
02:34 Swift completes circuits rapidly.
02:37 Swift used a technique called deep reinforcement learning to find the optimal commands to hurdle
02:43 around the circuit.
02:44 Because the method relies on trial and error, the drone crashed hundreds of times in training.
02:51 But since it was a simulation, the researchers could simply restart the process.
02:55 Analysis of the races showed that Swift was consistently faster at the start of a race
03:01 and pulled tighter turns than the human pilots.
03:04 The quickest lap from Swift came in at 17.47 seconds, half a second faster than the fastest
03:12 human pilot.
03:13 A key advancement with Swift is that it can cope with real-world challenges, such as aerodynamic
03:19 turbulence, camera blur, and changes in illumination, which can confuse systems that attempt to
03:25 follow a pre-computed trajectory.
03:28 This victory is indeed a rare moment in the evolution of artificial intelligence, and
03:33 perhaps more such incidents would become common with time's ebb and flows.
03:38 you