No abstract

The Deep Space One (DS1) mission, scheduled to fly in 1998, will be the first NASA spacecraft to feature an on-board planner. The planner is part of an artificial intelligence based control architecture that comprises the planner/scheduler, a plan execution engine, and a model-based fault diagnosis and reconfiguration engine. This autonomy architecture reduces mission costs and increases mission quality by enabling high-level commanding, robust fault responses, and opportunistic responses to serendipitous events. This paper describes the on-board planning and scheduling component of the DS1 autonomy architecture.

This paper demonstrates that Magill's method of structure adaptation can be incorporated into the framework of hierarchical estimation and system identification. The associated reduction in computational requirements potentially allows efficient parallel processing of these algorithms for use with ayeterns of high dimension.