Air Force selects Stratom to develop a machine learning-driven system for asset tracking.

Stratom announced its selection to develop an Autonomous Asset Tracking System — or AATS — utilizing artificial intelligence and machine learning for camera systems to accurately identify and track military logistics assets across various environments and modes of transport.

“Our innovative software stack leverages the latest advances in machine learning to detect and transcribe airplane tail numbers and determine which plane the tail number is associated with. Next, we’ll be able to communicate that information to databases and AGVs to refuel or load the aircraft autonomously,” said Elizabeth Gilmour, senior robotics perception engineer at Stratom. “By eliminating the complexities and uncertainties associated with traditional asset tracking systems, our streamlined, modification-free solution simplifies distributed operations while addressing imminent logistics challenges created by adopting the ‘Agile Combat Employment’ concept.”

Stratom’s initial phase of the Small Business Innovation Research project focuses on the software component, laying the groundwork for a suite of machine learning models that will process images to extract data such as asset type and identification numbers. With this approach, the leading developer of autonomous ground vehicles and robotic systems for commercial and defense applications eliminates the need for physical modifications to current assets, offering a cost-effective and highly scalable solution for logistics operations. In addition to automated asset tracking, the new technology simplifies the orchestration of logistics equipment for cargo, munitions, and refueling on the flight line.

Initially envisioned as a system to help autonomous refueling and cargo-loading vehicles identify the correct aircraft, AATS has received interest from several groups for other potential applications. The text spotting could uniquely identify airplanes and any asset with an identifying number, such as rail cars, trailers, or pallets. Further, other customers have shown interest in using this capability to identify relevant text in various operating situations.

“Our vision with the AATS extends beyond current logistics challenges. Building on our existing machine learning capabilities in object detection and text recognition, we’re solving today’s problems and anticipating the future needs of a rapidly evolving global market,” said Mark Gordon, president and CEO of Stratcom. “This unique solution sets the stage for our machine learning-powered system to seamlessly integrate into various sectors across military and commercial applications, providing unprecedented tracking accuracy and operational efficiency.”

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