Joint Optimization of Age of Information and Energy Consumption in UAV Trajectory Planning

With the advancement of technology, the application of unmanned aerial vehicles (UAVs) in emergency communications and disaster response have received widespread attention, especially in emergency situations such as natural disasters where traditional communication cannot transmit information in a timely and effective manner. This paper investigates the auxiliary communication of UAVs to ground equipment in disaster response scenarios, focusing particularly on the problem of optimizing UAV trajectories to minimize the Age of Information (AoI). We propose a multi-agent control trajectory and communication algorithm (MACTC) to improve learning efficiency and performance, addressing the dual challenges of information timeliness and energy consumption in drone networks. The study demonstrates that optimizing UAV service allocation and trajectory design can significantly reduce the AoI and save energy. Simulation results show that, compared to existing algorithms, MACTC offers significant advantages in reducing AoI and energy consumption, providing an effective solution for UAV network performance optimization.