Memory-Efficient Onboard Rock Segmentation
TBMG-17253
09/01/2013
- Content
Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gather ing Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations (see figure). Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions.
- Citation
- "Memory-Efficient Onboard Rock Segmentation," Mobility Engineering, September 1, 2013.