基于动态能耗的多无人机协同任务分配  

Collaborative Multi-UAV Tasking Based on Dynamic Energy Consumption

作　　者：史晓田 张宏立[1] 董颖超 SHI Xiao-tian;ZHANG Hong-li;DONG Ying-chao(College of Electrical Engineering,Xinjiang University,Urumqi Xinjiang 830017,Chi)

机构地区：[1]新疆大学电气工程学院,新疆乌鲁木齐830017

出　　处：《计算机仿真》2024年第3期25-32,127,共9页Computer Simulation

基　　金：新疆维吾尔自治区自然科学基金青年项目(2022D01C86);国家自然科学基金(51967019;52065064)。

摘　　要：针对多无人机物流配送存在的空载率高、能源利用效率低等问题,考虑同时送取货的多无人机配送场景和无人机实时能耗变化,提出了无人机动态能耗模型,进行了多无人机同时送取货任务分配问题的研究。用遗传算法对问题进行求解,针对经典遗传算法对初始种群的依赖性、易早熟、局部搜索能力弱等特点,设计了一种混合初始化方法,引入了食肉植物算法繁殖机制,并结合问题特性设计了内交叉策略和反馈变异策略,同时引入了过程精英策略,对遗传算法进行了改进。实验结果表明,改进的遗传算法可以有效求解基于动态能耗的多无人机任务分配问题。Aiming at the problems of high idle rate and low energy utilization efficiency of multi-drone logistics distribution,a dynamic energy consumption model of UAV is proposed considering the multi-drone distribution scenario of simultaneous delivery and pickup and the change of real-time energy consumption of UAVs,based on which the multi-drone simultaneous delivery and pickup task allocation problem is studied.The problem is solved by a genetic algorithm,and a hybrid initialization method is designed for the classical genetic algorithm's dependence on the initial population,easy premature maturity and weak local search ability,and a carnivorous plant algorithm reproduction mechanism is introduced,and the genetic algorithm is improved by designing an in-crossing strategy and a feedback variation strategy combined with the problem characteristics,and a process elite strategy is introduced.The experimental results show that the improved genetic algorithm can effectively solve the multi-UAV task assignment problem based on dynamic energy consumption.

关 键 词：多无人机 动态负载 能耗均衡 任务分配 遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]