The Curiosity rover and other spacecraft are learning to think for themselves
It takes up to 24 minutes for a signal to travel between Earth and Mars. If you’re a Mars rover wondering which rock to drill into, that means waiting at least 48 minutes to send images of your new location to NASA and then receive marching orders. It’s a lot of idle time for a robot that cost $2.6 billion to build.
That’s why engineers are increasingly giving spacecraft the ability to make their own decisions. Space robots have long been able to control certain onboard systems—to regulate power usage, for example—but artificial intelligence is now giving rovers and orbiters the ability to collect and analyze scientific data, then decide what info to send back to Earth, without any human input.
Since May 2016, NASA has been testing out an autonomous system on the Curiosity rover. A new report shows that the new system, named AEGIS (Autonomous Exploration for Gathering Increased Science), is working well, and has the potential to accelerate scientific discoveries.
“Right now Mars is entirely inhabited by robots,” says Raymond Francis, who’s part of Jet Propulsion Laboratory’s AEGIS software team, “and one of them is artificially intelligent enough to make its own decisions about what to zap with its laser.”
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The scientists taught AEGIS how to recognize bedrock, which they’re interested in because it contains clues into Mars’ past ability to support life. And 93 percent of the time, AEGIS chooses the same target a human would have chosen—but without the hour-or-so lag. It’s a big improvement over past measurements, which had ChemCam choose a target at random while waiting for NASA. Those analyses captured the best target only 24 percent of the time.
It takes about 90 to 105 seconds to target, zap, and analyze the findings, so the rover is already finished by the time NASA has new instructions for it. However, the team chooses not to run AEGIS if Curiosity’s batteries are running low, or there’s already too much data to beam back to Earth.
Curiosity’s mission is to understand the history of Mars’ Gale Crater, to figure out whether it was ever capable of sustaining life. “The way to do that is with a long-term survey,” says Francis. “AEGIS makes that survey richer by filling in the gaps… As of last week, we’re up to about 90 new locations that have been studied that otherwise would not have been. A lot of those results haven’t been published yet.”
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The AEGIS software was originally developed for the Opportunity rover in 2010, to help it identify and capture pictures of boulders. Since then, “we’ve improved its ability to discriminate specific materials,” says Francis. The team is also working on adding more flexibility in pointing, selecting targets, and initiating follow-up measurements.
And when NASA’s next rover lands on the red planet in 2020, it will be able to take AEGIS-guided measurements with any of the instruments on its mast. That includes its SuperCam, which is like ChemCam but with added capabilities—like a Raman spectrometer that analyses crystal structures, and visible and infrared spectrometers that work from a distance. “So we’ll have a whole suite of instruments we can point with AEGIS in 2020,” says Francis.
Beyond Mars
In a second paper in Science Robotics, Steve Chien from Jet Propulsion Laboratory’s Artificial Intelligence Group expounds on how intelligent systems are opening up a new era of space exploration.
Satellites orbiting Earth are already able to recognize snow versus water or ice and notice when those things change. They can analyze images as they collect them, to detect unusual events like an erupting volcano or fires or flooding, and then take action by collecting new images and data. For spacecraft further from Earth, not waiting for a command makes it easier to study short-lived phenomena like dust devils on Mars or jets of gas erupting out of a comet.
Since there isn’t always much bandwidth to send information back home, today’s spacecraft can interpret the data they collect, deciding which information is important enough to send back to Earth.
Not only do A.I. systems reduce idle time, but they can open up new capabilities. “In the future, orbiters, rovers, and aerial vehicles could autonomously organize and coordinate to better explore distant worlds,” writes Chien. Translation: swarmbots. On other planets.
And without robotic autonomy, exploring worlds like Europa, whose inner ocean might be able to sustain life, would be nearly impossible. In its orbit around Jupiter, this moon is very far from Earth, so the time delay is much worse than for Mars. Making matters more challenging, the radiation on Europa is severe, so the spacecraft will only be able to survive on the moon’s surface for a limited time before its electronics fry. So robots that can make their own decisions might be key on Europa.
Read rest at Popular Science