State-variable planning under structural restrictions: algorithms and complexity
Artificial Intelligence
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
A power-aware, satellite-based parallel signal processing scheme
Power aware computing
Constraint-Based Attribute and Interval Planning
Constraints
Mexar2: AI Solves Mission Planner Problems
IEEE Intelligent Systems
The deterministic part of IPC-4: an overview
Journal of Artificial Intelligence Research
COLIN: planning with continuous linear numeric change
Journal of Artificial Intelligence Research
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Flight controllers manage the orientation and modes of eight large solar arrays that power the International Space Station (ISS). The task requires generating plans that balance complex constraints and preferences. These considerations include context-dependent constraints on viable solar array configurations, temporal limits on transitions between configurations, and preferences on which considerations have priority. The Solar Array Constraint Engine (SACE) treats this operations planning problem as a sequence of tractable constrained optimization problems. SACE uses constraint management and automated planning capabilities to reason about the constraints, to find optimal array configurations subject to these constraints and solution preferences, and to automatically generate solar array operations plans. SACE further provides flight controllers with real-time situational awareness and what-if analysis capabilities. SACE is built on the Extensible Universal Remote Operations Planning Architecture (EUROPA) model-based planning system. EUROPA facilitated SACE development by providing model-based planning, built-in constraint reasoning capability, and extensibility. This article formulates the planning problem, explains how EUROPA solves the problem, and provides performance statistics from several planning scenarios. SACE reduces a highly manual process that takes weeks to an automated process that takes tens of minutes.