面向城市应急物资配送的多无人机协同路径规划算法  

Multi-UAV cooperative path planning algorithm for urban emergency material distribution

作　　者：于彦鹏 余墨多 汤奇荣 范勤勤 YU Yan-peng;YU Mo-duo;TANG Qi-rong;FAN Qin-qin(Logistics Research Center,Shanghai Maritime University,Shanghai 201306,China;Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education,Shanghai Jiao Tong University,Shanghai 200240,China;Laboratory of Robotics and Multibody System,Tongji University,Shanghai 201804,China)

机构地区：[1]上海海事大学物流研究中心,上海201306 [2]上海交通大学电力传输与功率变换控制教育部重点实验室,上海200240 [3]同济大学机器人技术与多体系统实验室,上海201804

出　　处：《控制与决策》2025年第4期1098-1106,共9页Control and Decision

基　　金：教育部人文社科基金规划基金项目(23YJAZH029);上海市浦江人才计划项目(22PJD030);国家自然科学基金项目(61603244)。

摘　　要：当城市发生突发性事件时,高效的应急物资配送能力是降低生命和财产损失的有效途径之一.为了提高城市应急物资配送效率和效果,提出一种基于进化多任务的多无人机协同路径规划算法(MCPP-EMTO).首先,将原多无人机应急配送问题作为主任务,并将不考虑无人机续航能力和容量约束的多无人机应急配送问题当作辅助任务;然后,所提出算法将辅助任务得到的有用演化信息迁移至主任务来提高求解效率;最后,为了验证所提出算法的性能,设置3个不同的城市应急配送场景,并选用4种高性能多目标进化算法作为比较算法.仿真实验表明,相比于4种比较算法,所提出算法能够得到多样性和逼近性较好的帕累托前沿.When emergencies occur in cities,efficient emergency material distribution capabilities are one of the effective ways to reduce losses of life and property.To improve the efficiency and effectiveness of urban emergency supply distribution,a multi-UAV cooperative path planning algorithm based on evolutionary multi-task optimization(MCPP-EMTO)is proposed.In this algorithm,the original multi-UAV emergency distribution problem is regarded as the main task,while the multi-UAV emergency distribution problem disregarding endurance and capacity constraints of UAVs is regarded as an auxiliary task.Moreover,the proposed algorithm transfers the useful evolutionary information from the auxiliary task to the main task to improve the solution efficiency.In order to verify the performance of the proposed algorithm,three different urban emergency distribution scenarios are used,and four high-performance multiobjective evolutionary algorithms are selected as comparison algorithms.Simulation experiments show that compared with the four comparison algorithms,the proposed algorithm can obtain Pareto fronts with better diversity and approximation under different scenarios.

关 键 词：无人机 三维路径规划 进化多任务 应急物流 进化计算 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] V279[自动化与计算机技术—控制科学与工程] V249[航空宇航科学与技术—飞行器设计]