A delay-aware multi-agent RL framework for active visual triangulation shows that Age-of-Information metadata, perception-consistent rewards, and multi-source covariance propagation each improve cooperative target localization under realistic communication delays.
Multi-robot system for autonomous cooperative counter-uas missions: Design, integration, and field testing,
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Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS
A delay-aware multi-agent RL framework for active visual triangulation shows that Age-of-Information metadata, perception-consistent rewards, and multi-source covariance propagation each improve cooperative target localization under realistic communication delays.