Pasadena, CA – Sometime between March 2010 and May 2012, a meteor streaked across the Martian sky and broke into pieces, slamming into the planet's surface. The resulting craters were relatively small – just 13 feet (4 meters) in diameter. The smaller the features, the more difficult they are to spot using Mars orbiters. But in this case – and for the first time – scientists spotted them with a little extra help: artificial intelligence (AI). It's a milestone for planetary scientists and AI researchers at NASA's Jet Propulsion Laboratory in Southern California, who worked together to develop the machine-learning tool that helped make the discovery.
A team of planetary scientists and AI researchers at NASA's Jet Propulsion Laboratory in Southern California tapped artificial intelligence to identify fresh craters on Mars. The High-Resolution Imaging Science Experiment (HiRISE) camera aboard NASA's Mars Reconnaissance Orbiter (MRO) spotted the craters. AI technology first discovered the craters in images taken the orbiter's Context Camera, then scientists followed up with the HiRISE image to confirm the craters. The accomplishment offers hope for both saving times and accelerating the volume of findings, as noted by NASA's Jet Propulsion Laboratory. According to the laboratory, scientists typically spend hours each day studying images captured by NASA's MRO, looking for changing surface phenomena like dust devils, avalanches, and shifting dunes.
The Mars Reconnaissance Orbiter's HiRISE camera captured this impact crater on Mars. On July 15, 1965, the Mariner 4 spacecraft snapped a series of photographs of Mars during its flyby of the Red Planet. These were the first "close-up" images taken of another planet from outer space, according to NASA. One of these first grainy photographs depicted a massive crater nearly 100 miles in diameter. Now, NASA's Jet Propulsion Laboratory (JPL) is tapping artificial intelligence (AI) to help with its cosmic cartography efforts, using these technologies to identify "fresh craters" on Mars.
Amid NASA's progress in AI research starting from ML model to predict hurricanes to partnering with Google to make quantum computing accessible, it has now developed a new AI tool to classify a cluster of craters on Mars. The launch of this new AI tool, built on a machine learning algorithm, was aimed at helping scientists to reduce their process time of scanning a single Context Camera image. Thus, researchers from Jet Propulsion Laboratory (JPL), created this tool also called an "automated fresh impact crater classifier", where for the "first time" researchers are leveraging AI to identify unknown craters on the Red Planet, stated by NASA, in their statement. According to their news release, typically scientists and researchers spend hours each day studying images to understand "dust devils, avalanches, and shifting dunes," and approximately 40 minutes to scan a single Context Camera image; however this tool will significantly reduce the processing time and advance the workflow massively. The launch of this tool is a part of a broader NASA's bigger effort -- COSMIC -- capturing onboard summarization to monitor image change that develops technologies for future generations of Mars orbiters.
An innovative artificial intelligence (AI) tool developed by NASA has helped identify a cluster of craters on Mars that formed within the last decade.The new machine-learning algorithm, an automated fresh impact crater classifier, was created by researchers at NASA's Jet Propulsion Laboratory (JPL) in California -- and represents the first time artificial intelligence has been used to identify previously unknown craters on the Red Planet, according to a statement from NASA. Scientists have fed the algorithm more than 112,000 images taken by the Context Camera on NASA's Mars Reconnaissance Orbiter (MRO). The program is designed to scan the photos for changes to Martian surface features that are indicative of new craters. In the case of the algorithm's first batch of finds, scientists think these craters formed from a meteor impact between March 2010 and May 2012. Related: Latest photos from NASA's Mars Reconnaissance Orbiter"AI can't do the kind of skilled analysis a scientist can," Kiri Wagstaff, JPL computer scientist, said in the statement.