AI-based C-UAV Swarm Defense
Artificial Twin developed a high-fidelity, simulation-based RL control system to support decision-making in drone defense scenarios involving large-scale kamikaze UAV swarms. Designed as a threat-prioritization and coordination layer, the RL policy learned to minimize zone damage more effectively than traditional heuristics, demonstrating adaptability under uncertainty and noisy input conditions. Problem Context With the rapid rise of low-cost autonomous UAVs, defense systems must now contend with the possibility of large-scale kamikaze drone attacks that overwhelm conventional rule-based responses.