involves very different classes of constraints and preferences, but once plans are generated they are relatively Abstract-Planning and scheduling for space operations stable. A prototype application has been developed that entails the development of applications that embed intimate separately supports Crew planning and Power planning for domain knowledge of distinct areas of mission control, the International Space Station (ISS). Domain requirements while allowing for significant collaboration among them.have been modeled in a significant level of detail, and The separation is useful because of differences in the loosely-coupled integration has been demonstrated in a planning problem, solution methods, and frequencies of rerealistic scenario. The integration is enabled by planning that arise in the different disciplines. For example, implementing a generic collaboration architecture that can planning the activities of human spaceflight crews requires be used to coordinate the work of any number of planning some reasoning about all spacecraft resources at timescales domains. The architecture is used to integrate two different of minutes or seconds, and is subject to considerable planners employing different underlying algorithms and volatility. Detailed power planning requires managing the data structures, by means of mapping the overlapping facets complex interplay of power consumption and production, of the plans.

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n The challenging timeline for DARPA's Orbital Express mission demanded a flexible, responsive, and (above all) safe approach to mission planning. Mission planning for space is challenging because of the mixture of goals and constraints. Every space mission tries to squeeze all of the capacity possible out of the spacecraft. For Orbital Express, this means performing as many experiments as possible, while still keeping the spacecraft safe. Keeping the spacecraft safe can be very challenging because we need to maintain the correct thermal environment (or batteries might freeze), we need to avoid pointing cameras and sensitive sensors at the sun, we need to keep the spacecraft batteries charged, and we need to keep the two spacecraft from colliding ... made more difficult as only one of the spacecraft had thrusters. Because the mission was a technology demonstration, pertinent planning information was learned during actual mission execution. For example, we didn't know for certain how long it would take to transfer propellant from one spacecraft to the other, although this was a primary mission goal. The only way to find out was to perform the task and monitor how long it actually took. This information led to amendments to procedures, which led to changes in the mission plan. In general, we used the ASPEN planner scheduler to generate and validate the mission plans. ASPEN is a planning system that allows us to enter all of the spacecraft constraints, the resources, the communications windows, and our objectives. ASPEN then could automatically plan our day. We enhanced ASPEN to enable it to reason about uncertainty. We also developed a model generator that would read the text of a procedure and translate it into an ASPEN model. Note that a model is the input to ASPEN that describes constraints, resources, and activities. These technologies had a significant impact on the success of the Orbital Express mission. Finally, we formulated a technique for converting procedural information to declarative information by transforming procedures into models of hierarchical task networks (HTNs). The impact of this effort on the mission was a significant reduction in (1) the execution time of the mission, (2) the daily staff required to produce plans, and (3) planning errors. Not a single misconfigured command was sent during operations.

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