Using iterative repair to automate planning and scheduling of shuttle payload operations

Authors:
Gregg Rabideau;Steve Chien;Jason Willis;Tobias Mann
Affiliations:
-;-;-;-
Venue:
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Year:
1999

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Abstract

This paper describes the DATA-CHASER Automated Planner/Scheduler (DCAPS) system for automated generation and repair of command sequences for the DATA-CHASER shuttle payload. DCAPS uses general Artificial Intelligence (AI) heuristic search techniques, including an iterative repair framework in which the system iteratively resolves conflicts with the state, resource, and temporal constraints of the payload activities. DCAPS was used in the operations of the shuttle payload for the STS-85 shuttle flight in August 1997 and enabled an 80% reduction in mission operations effort and a 40% increase in science return.