Defense Intelligence Swarm Research Center

To apply intelligent swarming systems to defense weapon systems, this project aims to develop a comprehensive software and hardware platform that enables decision-making and collaboration within intelligent swarms. The project will also include the development of core enabling technologies and the training of skilled personnel.

Development of Centralized GCS Command and Control Architecture

• Research on optimal initial deployment and mission assignment strategies for drones and UAVs operating as a swarm.
• AI-based optimization of a centralized Ground Control Station (GCS) for managing deployment and mission allocation in swarm scenarios.

Development of Manned-Unmanned Teaming (MUM-T) Engagement and Collaboration Systems

• Study on interpreting command intent of human operators to enable effective engagement by unmanned systems.
• Development of cooperative engagement frameworks under uncertainty through decision-making algorithms for manned-unmanned swarm collaboration.

Development of Embodied AI for Autonomous Swarm Cooperation

• Research on Multi-Agent Reinforcement Learning (MARL) for autonomous and efficient task execution by large-scale swarm systems.
• Exploration of AI methods that ensure safety and interpretability in autonomous cooperative behaviors.
• Lightweight implementation and deployment of AI algorithms for onboard execution in UAVs/drones.

Application-Oriented Development for Intelligent Swarm Systems

• Demonstration and analysis of multi-target surveillance missions using intelligent swarm systems, including optimal positioning and path planning for target coverage.
• Research on multi-target defense operations and neutralization attack strategies using autonomous swarm agents.