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Goal‐driven automation of a deep space communications station: a case study in knowledge engineering for plan generation and execution
Author(s) -
Hill, Jr. Randall W.,
Chien Steve A.,
Fayyad Kristina V.
Publication year - 1998
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00073
Subject(s) - automation , computer science , plan (archaeology) , software , process (computing) , nasa deep space network , software engineering , systems engineering , process automation system , embedded system , operating system , engineering , mechanical engineering , archaeology , spacecraft , history , aerospace engineering
This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services. In particular this paper describes: (1) the overall automation architecture, (2) the plan generation and execution monitoring AI technologies used and implemented software components, and (3) the knowledge engineering process and effort required for automation. This automation was demonstrated in February 1995, at the DSS13 Antenna Station in Goldstone, CA on a series of Voyager tracks and the technologies demonstrated are being transferred to the operational Deep Space Network stations.