Artificial intelligence, or AI, has enormous potential to change the way NASA’s spacecraft study the universe. But because all machine learning algorithms require training from humans, a recent project asks members of the public to label features of scientific interest in imagery taken by NASA’s Perseverance Mars rover.
Called AI4Mars, the project is the continuation of one launched last year that relied on imagery from NASA’s Curiosity rover. Participants in the earlier stage of that project labeled nearly half a million images, using a tool to outline features like sand and rock that rover drivers at NASA’s Jet Propulsion Laboratory typically watch out for when planning routes on the Red Planet. The end result was an algorithm, called SPOC (Soil Property and Object Classification), that could identify these features correctly nearly 98% of the time.
SPOC is still in development, and researchers hope it can someday be sent to Mars aboard a future spacecraft that could perform even more autonomous driving than Perseverance’s AutoNav technology allows.