Using Iterative Repair to Automate Planning and Scheduling of Shuttle Payload Operations

Gregg Rabideau and Steve Chien, Jet Propulsion Laboratory; Jason Willis, University of Colorado; Tobias Mann, Jet Propulsion Laboratory

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.


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