A Data Collection Decision-Making Framework for a Multi-Tier Collaboration of Heterogeneous Orbital, Aerial and Ground Craft

An algorithm for the autonomous identification of and tasking to collect additional data required to complete a goal is presented. This assertion-form goal is decomposed autonomously into an initial set of data collection tasks. Once these are completed, information gaps may exist or new information collection requirements may be identified. A utility-maximization, cost-minimization metric is applied to ascertain what data collection tasks craft should be assigned. This decision making process is performed at each level of the hierarchy, decomposing large-scale needs into progressively smaller assignments. The utility of this control approach is assessed for persistent surveillance and planetary science applications.