Computer Science – Artificial Intelligence
Scientific paper
Mar 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994spie.2244....2g&link_type=abstract
Proc. SPIE Vol. 2244, p. 2-9, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, Wray Buntine; Doug H. F
Computer Science
Artificial Intelligence
1
Scientific paper
For the past fifteen years, the International Ultraviolet Explorer (IUE) astronomical satellite has been successfully scheduled by `coarse-graining' the time into large discrete blocks. The success is due in part to the flexibility of coarse-graining which allows real-time modifications to the observing plan by the guest investigators. Such flexibility is desirable whenever an astronomical object is observed for the first time by a particular mission, since new data sometimes contain scientific surprises, and because several important types of astronomical objects are characteristically unpredictable and variable (e.g. supernovas, x-ray transients, etc.). Software which can incorporate this approach has the potential of significantly improving the efficiency and scientific return of future satellite missions. We give an overview of the IUE satellite and its scheduling requirements and describe our approach to satellite scheduling using constraint logic programming. We describe some of the constraints which are useful for satellite scheduling and show how the constraints can be used for efficient coarse- grained scheduling. We also discuss advantages of this approach for other satellite telescopes.
Graves Mark
McCollum Bruce
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