AI RESEARCH
Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments
arXiv CS.LG
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ArXi:2506.21129v2 Announce Type: replace Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation. However, global navigation satellite system (GNSS) spoofing attacks can induce out-of-distribution observation shifts that corrupt value estimation and degrade mission performance. Existing robust RL approaches typically improve resilience against specific attack models but often fail to generalize to attacks not encountered during