Shengyue Zhou

Safe multi-agent motion planning in presence of FDIAs via Kalman filter and filtered reinforcement learning

This paper studies safe motion planning for multi-agent systems in complex environments under Gaussian noise and false data injection attacks (FDIAs). Such attacks corrupt sensor measurements, degrade state estimation, and impair collision avoidance. To address this problem, we propose a unified framework for secure es...