Using abstraction to coordinate multiple robotic spacecraft

The trend toward multiple-spacecraft missions requires autonomous teams of spacecraft to coordinate their activities when sharing limited resources. The paper describes how an iterative repair planner/scheduler can reason about the activities of multiple spacecraft at abstract levels in order to greatly improve the scheduling of their use of shared resources. By finding consistent schedules at abstract levels, refinement choices can be preserved for use in robust plan execution systems. We present an algorithm for summarizing the metric resource requirements of an abstract activity based on the resource usages of its potential refinements. We find that reasoning about this summary information and that of state constraints can offer exponential improvements in the time to find consistent schedules with an iterative repair planner. We analytically describe the conditions under which these improvements are made and show that sometimes the extra overhead involved does not warrant their use. We apply these techniques within the ASPEN planner/scheduler to a domain where a team of rovers must coordinate their schedules to avoid conflicts over shared resources. Experiments using the ASPEN planner/scheduler in a Mars multi-rover domain support our analyses and compare techniques for controlling decomposition.