面向元启发式算法的多无人机路径规划现状与展望  

Research and development trend of multi-UAV path planning based on metaheuristic algorithm

作　　者：赵畅 刘允刚[1] 陈琳 李峰忠 满永超[1] ZHAO Chang;LIU Yun-gang;CHEN Lin;LI Feng-zhong;MAN Yong-chao(School of Control Science and Engineering,Shandong University,Jinan 250061,China)

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《控制与决策》2022年第5期1102-1115,共14页Control and Decision

基　　金：国家自然科学基金项目(62033007,61873146,62073192,61973186,61821004);山东省泰山学者攀登计划项目;山东省重大科技创新工程项目(2019JZZY010433)。

摘　　要：多无人机路径规划是一个复杂的多约束组合优化问题,通过传统算法很难求得优良结果,元启发式算法由于其快速高效而成为解决该类优化问题的有效手段.首先,针对多无人机路径规划的关键要素提出一种新的分类方法;其次,从算法改进方式入手,对各项研究中所采用的元启发式算法进行分类梳理,阐述它们的应用效果和优缺点,并根据所提出的分类方法和研究特点归纳了当前的研究成果;最后,结合目前多无人机路径规划研究存在的问题对未来发展趋势进行展望.Multi-UAV path planning is a complex multi-constraint combinatorial optimization problem,which is difficult to obtain good results through traditional algorithms.Recently,the metaheuristic algorithm has become an effective means to solve this kind of optimization problems because of its high efficiency.Firstly,a new classification method is proposed for the key elements of multi-UAV path planning.Then,we classify and discuss the improvement methods of metaheuristic algorithms used in the research results,elaborate the application performance,advantages and disadvantages of these algorithms,and summarize the current research results according to the proposed classification methods and research characteristics.Finally,the future development trend is prospected based on the existing problems in the current multi-UAV path planning research.

关 键 词：多无人机 路径规划 元启发式算法 算法改进 协同性 任务分类 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]