While Autonomous Guided Vehicles (AGVs) are poised to quickly become a crucial resource to the commercial logistics market, the United States Armed Forces is also looking towards implementing state-of-the-art intelligent automated systems to supplement their materiel handling processes and simultaneously improve airmen safety and operational efficiency. The Air Mobility Command (AMC), a MAJCOM of the U.S. Air Force, transports over 300,000 tons of cargo annually and the U.S. military logistics market is expected to grow to around $527 billion by 2027. Despite the acceleration of automation in manufacturing and logistics operations, commercial AGV solutions are not up to the task of meeting either required performance nor the challenging dynamic environments required by the U.S. Armed Forces. Emerging Autonomous Material Handling System (A-MHS) are limited to simple mission objectives in relatively static environments. Urbineer is developing a next generation A-MHS that can be easily scaled and tailored to complex mission objectives. The machine learning (ML) and open architecture autonomy platform is being developed from the ground up to perform Multivehicle Collaboration in complex real-world scenarios. Urbineer Mission Modular Platform utilizes the same open architecture autonomy system with a scalable chassis design, designed to be scalable and adapted to different âend-userâ variants. By leveraging Urbineerâs ongoing development, the DoD can tailor high fidelity MHS for multiple mission objectives while leveraging the cost and development benefits of an ongoing open architecture plat
