All Domain Convergence Applied Research

The All Domain Convergence Applied Research program, executed by the Army Research Laboratory (ARL), focuses on advancing technologies that enhance operational capabilities across multiple domains. The primary goal is to assess the feasibility of emerging technologies in real-world environments, allowing for rapid adaptation and improvement of systems to ensure interoperability and scalability. This research supports the Department of Defense's Combined Joint All-Domain Command and Control (CJADC2) initiative, aiming to optimize both lethal and non-lethal effects through the integration of artificial intelligence and machine learning. The program aligns with the Army Modernization Strategy and complements other efforts such as Next Generation Combat Vehicle Technology and Network C3I Technology.

The Collaborative Convergence Applied Research project within this program aims to reduce the time from sensor detection to shooter engagement. By leveraging AI algorithms and advanced data processing methods, this project seeks to enhance decision-making capabilities in multi-domain operations. The research focuses on developing architectures for AI-enabled decision support, which are crucial for mission command and achieving sensor-to-shooter dominance. This work is consistent with the priorities set by the Under Secretary of Defense for Research and Engineering.

One key area of research under this program is AI-Enabled Decision Support in Distributed Networks. This effort involves modeling complex tactical networks to develop training datasets that enhance AI decision support capabilities. Future plans include exploring real-time human-in-the-loop feedback processes to improve target detection accuracy and investigating multi-agent reinforcement learning techniques for basic fire and maneuver missions.

Another significant focus is on Synthetic Data for AI-Enabled Decision Support, which aims to incorporate synthetic data into training datasets to optimize AI performance in recognizing uncommon targets. Additionally, the program investigates Data Characterization for AI-Enabled Decision Support, focusing on data management techniques that ensure robust performance of AI systems across varied tactical environments. This includes developing methods for seamless data access across Department of Defense sources to facilitate continuous improvement of AI algorithms.

These efforts aim to enhance the Army's ability to conduct effective multi-domain operations by integrating cutting-edge technologies into its strategic framework.