With the rapid growth of the low-altitude economy, there is increasing demand for real-time data collection using UAV-assisted wireless sensor networks. This paper investigates the problem of minimizing the age of information (AoI) in UAV-assisted wireless sensor networks by optimizing the UAV flight routing. We formulate the AoI minimization task and propose a large language model (LLM)-assisted UAV routing algorithm (LAURA). LAURA employs an LLM as intelligent crossover operators within an evolutionary optimization framework to efficiently explore the solution space. Simulation results show that LAURA outperforms benchmark methods in reducing the maximum AoI, especially in scenarios with a large number of sensor nodes.

翻译：随着低空经济的快速发展，利用无人机辅助无线传感器网络进行实时数据采集的需求日益增长。本文研究了通过优化无人机飞行路径来最小化无人机辅助无线传感器网络中信息年龄的问题。我们形式化了信息年龄最小化任务，并提出了一种大语言模型辅助的无人机路由算法。该算法在进化优化框架内，将大语言模型作为智能交叉算子，以高效探索解空间。仿真结果表明，在降低最大信息年龄方面，所提算法优于基准方法，尤其在传感器节点数量较多的场景中优势更为明显。