UMD RoboScout aims to demonstrate a standoff sensing capability using COTS sensors placed on uncrewed air and ground mobile robotic platforms with AI-based casualty assessment algorithms that provide automated, real-time labeling of mass-casualty injuries in the field. The overall goal is to focus on assessing from a distance using non-contact, standoff signature acquisitions for the leading causes of preventable trauma death. The specific research objective is to apply tools from AI and perception, medical trauma and sensors, and robotics and autonomy to develop physiological signatures of severe injuries, data-driven models to detect them, and mobile platforms to collect the sensor data.