Picking a landing site for a Mars rover isn’t easy. The location has to be flat, lie at low elevation, and be free of dust and rocks, all so that the SUV-sized rover can touch down without crashing. The site must also be close to the region scientists want to study or else the slow-moving rover, which tools about at a tortoise’s pace, won’t reach its destination within the time frame of the mission.
But combing through detailed maps of the Martian surface to select the right site can take scientists years. And in the end, the selection process is very subjective. “We need something smarter,” says Guillaume Rongier of the Haystack Observatory at the Massachusetts Institute of Technology.
That’s why Rongier, a geologist, and Victor Pankratius, a computer scientist also at the Haystack Observatory, have developed a quicker, more systematic approach that uses artificial intelligence (AI), instead of humans, to mine the geographical data. Speaking last month at the fall meeting of the American Geophysical Union in New Orleans, Rongier presented the first maps of favorable locations found in this way.
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