The U.S. Military’s Artificial Intelligence Task Force (AITF) creating a new AI-enabled fight system to embrace future warfare, in response to a recent service information release.
The AITF is utilizing its technical expertise and proficiency with future expertise to work on an undertaking that could radically remodel how the U.S. army prepares for and conducts battlefield operations. It’s known as Aided Threat Recognition from Mobile Cooperative and Autonomous Sensors (ATR-MCAS), and it was the project focus for the AITF and Carnegie Mellon University’s National Robotics Engineering Center (CMU NREC) group which recently took part in a data assortment event at Fort Hunter Liggett from January 13-17.
ATR-MCAS is an AI-enabled system of networked, state-of-the-art air and ground autos that leverage sensors and edge computing.
The automobiles carry sensors enabling them to navigate within areas of curiosity to identify, classify, and geo-locate entities, hurdeles, and potential risks which reduces the cognitive load on Troopers.
The system can be able to aggregate and distribute the goal data, which may then be used to make recommendations and predictions based on the mixed threat picture given.
This ability to adapt to a number of performance requirements provides elevated situational consciousness and presents Soldiers with quicker decision-making skills.
Moreover, this adaptable design increases Soldier lethality and survivability by enabling Troopers to find, determine, and trace targets on the battlefield more swiftly.
For purposes such as ATR, data mediation focuses on shared consciousness at the tactical edge, which is essential to acquiring accurate data on the threat or object of interest.
Processing image data from many sensors via artificial intelligence and machine learning strategies require a huge quantity of computational power at the tactical edge, offering the Soldier more instant access to the data.