The US Aeronautics and Space Administration NASA has published a note with the intriguing headline “You Can Help Teach NASA Mars Rovers to Explore Mars Better.”
As the department explains, artificial intelligence has tremendous potential to change the way spacecraft study the universe. But since all machine learning algorithms require human training, NASA is asking members of the public to help identify elements of scientific interest in images taken by the Perseverance rover.
The project, called AI4Mars, is a follow-up to a project launched last year based on imagery from the Curiosity rover.
Early contributors to this project mapped out nearly half a million images, using a tool to highlight objects such as sand and rock that NASA’s Jet Propulsion Laboratory (JPL) Mars rover drivers typically look at when planning routes on the Red Planet. The end result was an algorithm called SPOC (Classification of Soil and Object Properties) that could correctly identify these features in almost 98% of cases.
The SPOC algorithm is still in development, and NASA hopes that one day it can be sent to Mars aboard a spacecraft of the future that can do more autonomous driving than Perseverance’s AutoNav technology allows.
AI4Mars now provides additional markers to indicate more precise details, allowing people to choose options such as moving rocks or nodules (globular mineral formations).
The goal is to hone an algorithm that could help a future rover pick “needles out of a haystack” of data sent from Mars.
Equipped with 19 cameras, Perseverance sends tens to hundreds of images to Earth every day for scientists and engineers to view specific geologic features. But time is running out: after these images have traveled millions of kilometers from Mars to Earth, NASA team members have hours to develop the next set of instructions, based on what they see in these images, to send to Perseverance.
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