Online route planning decision-making method of aircraft in complex environment
Aiming at the problem of online route planning for aircraft,an online autonomous decision-making method for aircraft based on deep reinforcement learning(DRL)is proposed.Firstly,the maneuvering model and detection model of the aircraft are explained,and then the deep deterministic policy gradient(DDPG)algorithm of DRL is employed to construct the frame of the aircraft policy model.On this basis,a curriculum learning(CL)-DDPG algorithm based on CL is proposed,which decomposes the online route planning task,guides the aircraft to learn the strategies of target approach,threat avoidance,and air route optimization.The corresponding Gaussian noises are set to help the aircraft explore and optimize the strategy.And,the adaptive learning and decision-making control of the aircraft in complex scenarios are realized.Simulation experiments show that the CL-DDPG algorithm can effectively improve the training efficiency of the model.The algorithm model has higher task success rate,excellent generalization and robustness,and can be better applied to online route planning tasks in complex dynamic environments.
万方数据
维普
