Paper
22 May 2013 A data collection decision-making framework for a multi-tier collaboration of heterogeneous orbital, aerial, and ground craft
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Abstract
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 utilitymaximization, 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.
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Jeremy Straub "A data collection decision-making framework for a multi-tier collaboration of heterogeneous orbital, aerial, and ground craft", Proc. SPIE 8742, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV, 87420R (22 May 2013); https://doi.org/10.1117/12.2019115
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Cited by 13 scholarly publications.
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KEYWORDS
Bacteria

Data processing

Unmanned aerial vehicles

Surveillance

Databases

Planetary science

Computer science

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