Automated observation scheduling for the VLT

Computer Science – Artificial Intelligence

Scientific paper

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Artificial Intelligence, Computer Programs, Scheduling, Very Large Array (Vla), Algorithms, Computer Techniques, Hubble Space Telescope, Neural Nets, Software Engineering, Space Observations (From Earth)

Scientific paper

It is becoming increasingly evident that, in order to optimize the observing efficiency of large telescopes, some changes will be required in the way observations are planned and executed. Not all observing programs require the presence of the astronomer at the telescope: for those programs which permit service observing it is possible to better match planned observations to conditions at the telescope. This concept of flexible scheduling has been proposed for the VLT: based on current and predicted environmental and instrumental observations which make the most efficient possible use of valuable time. A similar kind of observation scheduling is already necessary for some space observatories, such as Hubble Space Telescope (HST). Space Telescope Science Institute is presently developing scheduling tools for HST, based on the use of artificial intelligence software development techniques. These tools could be readily adapted for ground-based telescope scheduling since they address many of the same issues. The concept are described on which the HST tools are based, their implementation, and what would be required to adapt them for use with the VLT and other ground-based observatories.

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