NASA has pitted a professional drone racer against its AI.
The space agency took on pilot Ken Loo on a specially designed course using three purpose built drones named Batman, Joker and Nightwing.
While the human prevailed, NASA found its craft, which were funded by Google, were far more consistent – and didn’t suffer from tiredness.
The space agency took on pilot Ken Loo on a specially designed course using three purpose built drones named Batman, Joker and Nightwing in a project funded by Google. Loo averaged 11.1 seconds, compared to the drones 13.9 seconds
They pledged that future versions would compete in professional drone race.
‘We pitted our algorithms against a human, who flies a lot more by feel,’ said Rob Reid of NASA’s Jet Propulsion Laboratory in Pasadena, California, who led the project.
‘You can actually see that the A.I. flies the drone smoothly around the course, whereas human pilots tend to accelerate aggressively, so their path is jerkier.’
The race, held on Oct. 12 came after two years of research into drone autonomy funded by Google.
The company was interested in JPL’s work with vision-based navigation for spacecraft – technologies that can also be applied to drones.
To demonstrate the team’s progress, JPL set up a timed trial between their A.I. and world-class drone pilot Ken Loo.
The team built three custom drones (dubbed Batman, Joker and Nightwing) and developed the complex algorithms the drones needed to fly at high speeds while avoiding obstacles.
These algorithms were integrated with Google’s Tango technology, which JPL also worked on.
The drones were built to racing specifications and could easily go as fast as 80 mph (129 kph) in a straight line.
But on the obstacle course set up in a JPL warehouse, they could only fly at 30 or 40 mph (48 to 64 kph) before they needed to apply the brakes.
Compared to Loo, the drones flew more cautiously but consistently.
NASA says their algorithms are still a work in progress.
For example, the drones sometimes moved so fast that motion blur caused them to lose track of their surroundings.
Loo attained higher speeds and was able to perform impressive aerial corkscrews.
The obstacle course used in the race was set up in a JPL warehouse. The drones were built to racing specifications and could easily go as fast as 80 mph (129 kph) in a straight line. But on the obstacle course set up in a JPL warehouse, they could only fly at 30 or 40 mph (48 to 64 kph) before they needed to apply the brakes.
But he was limited by exhaustion, something the A.I.-piloted drones didn’t have to deal with.
‘This is definitely the densest track I’ve ever flown,’ Loo said.
‘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.’
While the A.I. and human pilot started out with similar lap times, after dozens of laps, Loo learned the course and became more creative and nimble.
For the official laps, Loo averaged 11.1 seconds, compared to the autonomous drones, which averaged 13.9 seconds.
While the A.I. and human pilot started out with similar lap times, after dozens of laps, Ken Loo learned the course and became more creative and nimble.
But the latter was more consistent overall.
Where Loo’s times varied more, the A.I was able to fly the same racing line every lap.
‘Our autonomous drones can fly much faster,’ Reid said.
‘One day you might see them racing professionally!’
These technologies might allow drones to check on inventory in warehouses or assist search and rescue operations at disaster sites.
They might even be used eventually to help future robots navigate the corridors of a space station.
