Another challenge of targeted science is fine pointing. Some of the most interesting features are the smallest ones – the calcium sulfate veins found in rocks along the rover’s traverse, for example, have revealed important insights into the chemistry of the watery environment in Gale’s past. But these veins are often less than 5 millimeters wide, meaning that a pointing error of only a fraction of a degree can mean missing them with ChemCam from a few meters away. It's hard to pinpoint such small targets. Our stereo model of the rover’s surroundings (made from NavCam images) has resolution limits, and we can only control the motion of the mast so precisely. With AEGIS, we can do autonomous pointing refinement, where the software can correct small errors in the pointing of observations commanded by the team on Earth, ensuring we hit the desired targets on the first try (and saving valuable time on Mars).

History

AEGIS originally began in the early 2000s as part of a JPL research project that was developing autonomy technology for future rover missions. This effort developed a large, integrated suite of rover technology that enabled a number of autonomous behaviors, including autonomous navigation, onboard commanding and re-planning, and autonomous science. The goal of the autonomous science element was to help scientists collect valuable science data at times when the rover wasn’t in frequent communication with Earth. Several planetary geologists worked closely with the project to help us design software that could autonomously identify scientific features (such as rocks) in visual images and decide which targets would be the most interesting to scientists. Project technology was tested extensively on multiple research rovers in the JPL Mars Yard. Testing of the autonomous science element, which was eventually called AEGIS, typically involved identifying various terrain features (e.g., volcanic rocks or an ancient river bed) during a rover drive and then working with other autonomy software to redirect rover activities towards collecting data on identified science targets.

Based on the results of this project, the Mars Exploration Rover (MER) Mission authorized AEGIS to be uploaded to the Opportunity rover in order to support autonomous selection of targets for remote sensing instruments. In 2009, AEGIS was successfully uploaded to Opportunity where it has been used to identify and acquire targets of interest for the narrow field-of-view MER Panoramic Camera. MER Pancam is a high-resolution, multi-spectral imager that acquires images at various wavelengths. These images help scientists learn more about the minerals found in Martian rocks and soils. AEGIS was used on MER to acquire Pancam data on rocks with certain properties at times where otherwise such data would not be possible. It has been used successfully on MER to acquire data on outcrop, cobbles, crater ejecta, and boulders.

ChemCam

Following the success of AEGIS on MER, new opportunities on the Mars Science Laboratory mission were explored, especially for the ChemCam instrument. ChemCam is a perfect candidate for AEGIS intelligent targeting. The instrument combines a laser-induced breakdown spectrometer (LIBS) system with a context camera called the remote micro-imager (RMI). The RMI has a very narrow field of view, about 1 degree in diameter. The LIBS focuses its powerful laser on rocks as far away as 7 meters from the rover, and captures spectra from the plasma produced. The spot measured is typically less than 1 millimeter across, so targeting is important – you want that spot to fall on something interesting.