Automation And Queue Management For Neo Surveying And Follow-Up

The Catalina Sky Survey (CSS) at the University of Arizona operates three telescopes full-time in the search for near-Earth objects (NEOs). CSS has discovered 47% of all known NEOs, reported over 46 million asteroid positions, and our photometry has been used to generate light curves for half a billion sources. Our telescopes are capable of highly automated data acquisition and we are working on making one of them autonomous from target selection to reporting of high-confidence data. I cover various aspects of the high-level automation at CSS, with emphasis on the queue manager software, and give a brief overview of CSS and our results.