Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments 事件

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments arXiv:2506.21129v2 Announce Type: replace-cross Abstract: 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 resil