Rover thinks for itself on Mars

Software that allows the Mars rover Opportunity to perform autonomous data collection and research on portions of the Martian surface recently was named NASA’s “Software of the Year” for 2011. The award was a cause of celebration for several local JPL techies who worked for years on the software’s algorithms.

AEGIS, which stands for Autonomous Exploration for Gathering Increased Science, has been operating on the rover since December 2009, directing onboard cameras to hone in on scientifically interesting elements of the planet’s surface. For it be recognized as the best software being used throughout NASA’s 10 facilities is no small honor, according to Ben Bornstein, a senior member of JPL’s Machine Learning and Instrument Autonomy Group.

“There’s internal competition first, and that competition, in and of itself, is very stiff,” Bornstein said, describing how the team first had to win at JPL, then win among all the other facilities across the nation. “We were very happy to be represented.”

La Cañada resident Michael Burl works with Bornstein as a principal member of the technical staff. On the AEGIS team, Burl helped develop an algorithm named “Rockster.” This front-end visual processing algorithm helps the rover identify the boundary contours of rocks, converting 1 million pixels into an image that can be read back on Earth.

“Subsequent components of the AEGIS software calculate features of the detected rock regions and rank the regions according to the preferences expressed by the mission science team,” Burl added.

Using AEGIS, team members provide the rover with a set of attributes to look for in rocks and other surface features, explained Bornstein, who lives in Sierra Madre.

“When it runs, it will search for things on outcroppings or something of interest. Then it will make a sort of a qualitative judgment based on those criteria,” he said.

The software strengthens the rover’s ability to “Follow the Water,” the overall mission of NASA’s Mars Exploration Rovers program, as it helps Opportunity identify calcitic rocks, like gypsum, that indicate the presence of water at the surface.