UAV target tracking method based on deep reinforcement learning

This study proposes a UAV target tracking method using reinforcement learning algorithm combined with GRU to promote UAV target tracking and visual navigation in complex environment. Firstly, an algorithm TD3 using deep reinforcement learning and the GRU gated loop unit are introduced. The unit is then added to the neural network to process continuous time data, and the algorithm TD3 is adopted to train the model so that it can drive the UAV to make autonomous flight decisions and accomplish target tracking. Finally, the proposed method is verified on the AirSim simulation platform.