Learn-to-Recover: Retrofitting UAVs with Reinforcement Learning-Assisted Flight Control Under Cyber-Physical Attacks
Fan Fei,Zhan Tu,Dongyan Xu,Xinyan Deng,Fan Fei,Zhan Tu,Dongyan Xu,Xinyan Deng
In this paper, we present a generic fault-tolerant control (FTC) strategy via reinforcement learning (RL). We demonstrate the effectiveness of this method on quadcopter unmanned aerial vehicles (UAVs). The fault-tolerant control policy is trained to handle actuator and sensor fault/attack. Unlike traditional FTC, this policy does not require fault detection and diagnosis (FDD) nor tailoring the co...
