Multi-Objective Distributed Real-Time Trajectory Planning for Gliding Aircraft Cluster

A new combat strategy that enables coordinated operations of gliding aircraft clusters for multi-target strikes imposes higher demands on the coordination, real-time responsiveness, and strike accuracy of gliding aircraft clusters. Due to the high speed and large inertia characteristics of gliding aircraft, traditional trajectory planning methods often face challenges such as long computation times and difficulty in responding to dynamic environments in real-time when dealing with large-scale gliding aircraft clusters. This paper proposes a distributed cooperative trajectory planning method for multi-target strikes by gliding aircraft clusters to address this issue. By introducing a multi-objective distributed real-time trajectory planning approach based on Multi-Agent Deep Deterministic Policy Gradients (MADDPG), the gliding aircraft execute distributed cooperative trajectory planning based on the trained model. Due to its robust real-time performance, the gliding aircraft do not need to recalculate trajectories for different initial positions of the cluster. Simulation results show that the average error between the gliding aircraft cluster and the target point is 2.1 km, with a minimum error of 0.06 km and a hit rate of 96.6%, verifying the significant advantages of this method in real-time planning capability and strike accuracy.