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The future operational environment will be contested in all domains in an increasingly lethal and expanded battlefield, conducted in complex environments against challenged deterrence. In order to prevail in the Multi-Domain Operations (MDO) phases of dis-integration, exploitation, and re-entry to competition, the Army will need to employ teams of highly-dispersed warfighters and agents (robotic and software), to include Robotic Combat Vehicles (RCVs). To operate as a high-functioning team, Soldiers will need to be able to coordinate with RCVs as if they were teammates (i.e. fellow Soldiers) rather than tools (i.e. tele-operated robots capable of performing limited tasks). To enable this human-agent teamwork, the Artificial Intelligence for Maneuver and Mobility (AIMM) Essential Research Project (ERP) aims to revolutionize AI-enabled systems for autonomous maneuver that can rapidly learn, adapt, reason, and act in MDO. The program is divided into two main Lines of Effort (LoE): Mobility, and Context-Aware Decision Making (CADM). The Mobility LoE is focused on developing resilient autonomous off-road navigation for combat vehicles at operational speed that can autonomously move to a position of advantage. The CADM LoE is focused on enabling autonomous systems to reason about the environment for scene understanding with the ability to incorporate multiple sources of information and quantify uncertainty. Ultimately, the Mobility and CADM LoE's will culminate in autonomous maneuver-the ability of unmanned vehicles to autonomously maneuver on the ground against a near-peer adversary within the Multi-Domain Operations (MDO) battlespace. This capability will enable autonomous vehicles to team with Soldiers more seamlessly (reducing Soldier cognitive burden); conduct reconnaissance to develop the enemy situation at standoff (creating options for the commander); and enabling the next generation of combat vehicles to fight and win against a near-peer adversary.
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