Anything you can do, AI can do better. Eventually.
On October 12, NASA put on its own demonstration, pitting an AI-piloted racing drone against world-renowned drone pilot Ken Loo.
Researchers at NASA’s Jet Propulsion Laboratory, who have spent the last two years working on drone autonomy (which was funded by Google), built three custom drones equipped with cameras for vision and algorithms that would help them fly at high speeds while still avoiding obstacles.
The drones, named Batman, Joker, and Nightwing, used algorithms that were integrated with Google’s Tango technology, which helps AI map out 3D spaces.
These drones could fly up to 80mph in a straight line, but on this particularly cramped course, were only able to hit 40mph.
In a press release, NASA explained the pros and cons of both the autonomous drones and the human pilot. While the AI-powered drones were able to fly more consistently, they were also more cautious and, at times, ran into problems with motion blur at higher speeds. On the other hand, Loo was able to learn the course after a few laps and fly with much more agility than the autonomous drones, but is susceptible to fatigue.
“This is definitely the densest track I’ve ever flown,” Loo said in the release. “One of my faults as a pilot is I get tired easily. When I get mentally fatigued, I start to get lost, even if I’ve flown the course 10 times.”
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[youtube https://www.youtube.com/watch?v=SrqrGweKQAU&w=560&h=315]
Long story short, the AI and the human started out with similar lap times, but Loo eventually won out and ended up with a faster average lap time than the AI.
The implications here are big: autonomous drones may eventually be used for surveillance, emergency response, or inventory in warehouses.
