面向应急场景最小化数据收集时间的无人机路径优化方法

Optimizing Unmanned Aerial Vehicle Paths to Minimize Data Collection Time in Emergency Scenarios

针对应急场景中无人机(Unmanned Aerial Vehicle,UAV)辅助物联网节点(Internet of Things Node,IoTN)收集数据过程数据时效性差的问题,提出了一种基于费马点最小化数据收集时间的UAV路径优化方法。费马点的选取能够有效地优化UAV飞行路径,从而使数据收集时间最小,确保收集数据的及时性。该方法通过路径离散化将UAV飞行路径分段,利用连续凸优化(Successive Convex Approximation,SCA)转化复杂混合整数问题的非凸约束,围绕节点的联通性,优化UAV飞行速度与悬停点,求解出最小化数据收集时间的飞行路径。仿真结果表明,所提方法在收集数据时间方面相较于传统方法有6%的提升。

In response to the challenges of poor data timeliness in the process of Unmanned Aerial Vehicle(UAV)assisted data collection from Internet of Things Node(IoTN)in emergency scenarios,this paper proposes a UAV path optimization method based on Fermat points to minimize data collection time.The selection of Fermat points effectively optimizes the UAV’s flight path,minimizing the time required for data collection and ensuring the timeliness of collected data.This method discretizes the UAV’s flight path,utilizes Successive Convex Approximation(SCA)to address the non-convex constraints of complex mixed-integer problems,and focuses on the connectivity of nodes.It optimizes flight speed and hover points to derive the flight path that minimizes data collection time.Simulation results indicate a 6%improvement in data collection time compared to traditional methods.