To address the optimization problem of flight trajectories and communication strategies in multi-UAV collaborative reconnaissance missions, this study proposes a collaborative planning approach based on deep reinforcement learning, considering diverse costs such as flight distance, communication energy consumption, and channel capacity, along with multiple constraints including base station channel resource constraints, UAV performance constraints, and collision avoidance constraints. Firstly, a collaborative planning model for multi-UAV trajectories and communication strategies is established for randomly unknown reconnaissance environments. Secondly, an end-to-end deep reinforcement learning framework based on the multi-agent proximal policy optimization algorithm is introduced to jointly optimize coupled variables such as UAV trajectories, communication connection strategies, and communication transmit power, with flight distance, communication energy consumption, and channel capacity serving as multiple optimization objectives. To reduce the complexity of learning and solving multi-objective tasks, a trajectory planning sub-model incorporating virtual gravity from base stations is designed, which decreases the decision space. A trajectory planning sub-model that incorporates the virtual gravitational force of base stations is designed based on the artificial potential field method. Through the approach of automatically optimizing parameters via reinforcement learning, the size of the decision space is reduced, and the convergence speed of the model is accelerated. Finally, simulation experiments demonstrate the advantages of the proposed method in optimizing the overall mission cost index.

To address the cooperative control problem of using spacecraft formation for approaching and flying around the non-cooperative target, a distributed prescribed performance control method based on the fully-actuated system theory is proposed in consideration of external interference and unexpected orbital maneuvers. First, a relative dynamic model for the service spacecraft formation and the non-cooperative target is established based on the line-of-sight coordinate system, and the fully-actuated control law is constructed to reduce the complexity of controller design. Furthermore, a distributed agreed-time prescribed performance controller is designed using the topology theory to ensure the control performance of the spacecraft formation around the target. In addition, an extended state observer is employed to observe and compensate for the uncertainties and disturbances in the system, thereby improving the control precision and robustness in spacecraft formation flying around the target. Finally, the effectiveness of the designed control method is verified by two sets of flying around simulations.