Real-time Assessment and Predictive Status (RAPS)

Robotic Combat Vehicles (RCV) offer significant tactical advantages for accomplishing missions while also keeping the warfighter safe in Multi-Domain Operations (MDO). However, this is only possible if the RCV can stay in the fight and the operators are confident in the system’s mission availability. Real-time Assessment and Predictive Status (RAPS) is an analytic that uses the best in breed Artificial Intelligence and Machine Learning (AI/ML) and Human Machine Teaming, building on Charles River Analytics’ core competency in probabilistic modeling and role-tailored interfaces. RAPS provides real-time prognostics and decision support, for RCV Operators, Field-Level Maintainers, and Commanders. This solution is designed to be maintainable and scalable for integration into a holistic sustainment solution that will execute on an entire fleet of RCVs under multiple modular mission payloads. Ultimately, this will reduce maintenance overhead, increase RCV mission availability, and improve operational readiness.