感-通-物多目标融合应急无人机路径规划方法

Integrated perception-communication-logistics multi-objective oriented path planning for emergency UAVs

为了完成多无人机应急救援场景下救灾点的需求感知(感)、数据收集(通)和物资投放(物)任务,提出了在考虑无人机能耗约束下,感-通-物多目标融合的两阶段的应急无人机路径规划求解框架。第一阶段提出基于时序图卷积网络的救灾点人数预测模型,并量化救灾点物资和通信需求;第二阶段提出基于贪心和禁忌搜索的多无人机路径规划算法,通过交替优化救灾点划分和单无人机路径规划来求解原优化问题。仿真结果表明,该算法在总服务收益上优于传统的无预测多无人机路径规划算法。

In order to complete the tasks of demand perception(perception),data collection(communication),and mate‐rial delivery(logistics)at disaster relief sites in multi-UAV emergency scenarios,a two-stage solution framework was proposed for multi-UAV path planning that integrated perception,communication,and logistics objective considering UAV energy consumption constraint.In the first stage,a temporal graph convolution networks-based model was intro‐duced to predict the number of personnel at the relief sites to quantify its supply and communication needs.In the second stage,a multi-UAV path planning algorithm based on the greedy and tabu search was proposed to solve the optimization problem through iteratively optimizing the relief point clustering and the path planning of individual UAV.The simula‐tion results demonstrate that the proposed algorithm is superior to the traditional prediction-free multi-UAV path plan‐ning algorithm in terms of the total service revenue.