Unmanned Surface Vehicle (USV) and Unmanned Underwater Vehicle (UUV) Autonomous Behavior Development

Research and Development (R&D) is proposed to design a novel Unmanned Vessel Health Monitoring System (UVHMS), providing an onboard diagnostics and prognostics system for USV and UUV platforms, supporting the identification of active and imminent platform faults.  Using onboard sensors and data processing, multi-sensor cross-correlation, pattern recognition and anomaly detection, the UVHMS will essentially replace the human sensors found aboard a manned vessel, allowing the USV/UUV to autonomously make data-driven health decisions, while also adding the capability to periodically provide real-time and predictive vessel health data back to remote stakeholders. Problem Statement: Advancements in autonomous operation, artificial intelligence and machine learning have led to proliferation of unmanned vehicles.  While these systems provide significant operational and safety advantages to U.S. future warfighters, they cannot rely on human senses to make decisions about their own health or detect an anomaly before a major malfunction occurs. Plan/Process Outline: Research and design will be performed investigating multi-sensor data fusion, using machine learning, to account for non-linear characteristics when multiple disparate sensors are cross-correlated for detection of abnormal situations or recognized problems.   The resulting prototype will be delivered to PM-406, integrated onto a designated asset, and tested. Standard engineering documentation (SRD, RTM, SAD, ICD, Test Plans, and Test Reports) will be developed and delivered throughout the process.