DNA-mRNA: Digital twin Novel Architecture study with Machine learning Research for Naval Applications

The U.S. Naval Services require a rapid force augmentation to meet growing threats from a variety of adversaries.  Unmanned assets such as UUVs are the only feasible approach for meeting the force augmentation demands in a reasonable budget and timeline.  In order to provide operationally useful capabilities, UUVs must be autonomous due to severe communication restrictions limiting human on- or in-the-loop control.  As an additional communication challenge, the commander must have operational visibility over underwater autonomous assets such that she understands the mission state, even in intermittent communication environments.  Digital twins are a modeling technology that, once adjusted for the underwater environment, can be augmented with machine learning and autonomy technologies to enable a variety of capabilities across a variety of missions relevant to the U.S. Navy.  We propose DNA-mRNA (Digital twin Novel Architecture study with Machine learning Research for Naval Applications), a study to identify how digital twins can enable critical capabilities for the U.S. Navy, and how these capabilities can be operationalized on autonomous undersea vehicles.  We will demonstrate that digital twins enable autonomous undersea systems to provide a variety of mission effects across a variety of missions, that they enable a commander to control, predict, and monitor an undersea system with communication constraints, and that they enable system adaptation to varying communication environments.