In mid-October, a NASA-developed software called AEGIS was uploaded to the Mars Science Laboratory (MSL) rover. The AEGIS technology, winner of NASA’s 2011 Software of the Year award, will soon allow scientists on the ground to more easily identify interesting rocks and other terrain features on the Red Planet.
Photonics & Imaging Technology spoke to two NASA software experts about how the Mars tool will help rovers become more autonomous.
Michael Burl of Jet Propulsion Laboratory assisted in the development of an AEGIS component known as ROCKSTER, a rock detection algorithm that analyzes images taken by the rover and identifies targets of interest. Tara Estlin, who supervises the Machine Learning and Instrument Autonomy group at the Jet Propulsion Laboratory, leads the AEGIS efforts.
Photonics & Imaging Technology: What is AEGIS?
Tara Estlin: With AEGIS, we analyze different types of images to pick out science targets with certain features or properties. Then, if we find science targets with those properties, we can automatically take measurements with the ChemCam Laser Induced Breakdown Spectrometer (LIBS), which identifies rock composition.
Michael Burl: The Laser Induced Breakdown Spectrometer (LIBS) is part of the MSL Curiosity rover’s ChemCam instrument package. The LIBS instrument shoots a laser at the rocks, vaporizes the material, and takes spectra of it; that [technology] could really benefit from this intelligent targeting that our software provides.
Estlin: The AEGIS software analyzes navigation camera images, which are wide-angle images showing a decently large area of the terrain. For these images, the software is mainly looking for rocks. We pull out information on their size, their shape, their relative intensity, or lightness or brightness in the image — all properties that we can pull out of a greyscale image. Then, we use that property information to prioritize what rocks to target first.
P&IT: What other kinds of images are possible?
Estlin: The software can also analyze what’s known as Remote Micro Imager (RMI) images. The RMI is another camera on the rover’s mast, actually part of the ChemCam instrument, which covers a much smaller area of terrain. For this imager, you can only get a couple of centimeters of the terrain in view, since it has a much smaller field of view. For those images, we’re looking for small features like veins, concretions, white spots, or pebbles.
P&IT: Why is it important to get this kind of terrain data?
Burl: With the software, the rocks get prioritized; the rover itself can then repoint its mast camera to look at, say, the highest-priority rock that it detected autonomously. That saves a huge amount of time; the other way of doing targeted observations like that is to send down images to the Earth, have scientists look at them, and then they’ll say, “We want to target this rock right here.” Then, they upload commands; that takes a couple days, with the communication cycles and accessibility. By doing all this target selection onboard — the rock detection, prioritization, retargeting — it saves a lot of time getting those targeted observations.
Estlin: The other benefit: When we’re analyzing RMI images and picking out these tiny targets, the ground [control] has actually seen the local area, and they see that there might be some interesting white veins in the area that they want to take ChemCam measurements on. But the veins are so small; they have a hard time accurately hitting them with ChemCam. Due to motor backlash and other pointing inaccuracies, it’s really hard to hit very small targets. AEGIS, using ROCKSTER, will pick out exactly where the veins are in the image and refine the pointing online. Now you can do the data acquisition all in one day. That saves several days of ground activities, which is very valuable time.