无人机集群任务规划方法研究综述

doi:10.3969/j.issn.1001-506X.2021.01.13

摘要/Abstract

摘要：

无人机集群以其高度的灵活性、广泛的适应性、可控的经济性,拥有越来越广泛的应用潜力,受到国内外的高度关注。任务规划是无人机集群应用的顶层规划，是根据任务环境态势、任务需求、自身特性等要求进行的综合调度，从而建立无人机与任务的合理映射关系，维持机间合理协同合作关系。本文从基于逻辑与规则的自上而下式任务规划和基于集群智能涌现的自下而上式任务规划两个方面,对无人机集群任务规划技术现状进行了全面的总结,分析了当前无人机集群任务规划技术研究应当关注的若干发展方向。本文的工作对于全面了解无人机集群任务规划技术现状具有重要参考意义。

关键词: 无人机集群, 任务规划, 群体智能, 集群行为, 研究现状

Abstract:

With the advantages of high flexibility, wide adaptability, and controllable economical efficiency, the unmanned aerial vehicle swarm has plenty of applications, and has attracted great attentions at home and abroad. Mission planning is the top-level planning of unmanned aerial vehicle cluster application. It is a compre-hensive scheduling according to the requirements of mission environment situation, task requirements and its own characteristics, so as to establish a reasonable mapping relationship between unmanned aerial vehi-cle and task, and maintain a reasonable cooperative relationship among unmanned aerial vehicles. The present situation of mission planning technology for the unmanned aerial vehicle is summarized comprehensively from two different aspects. One is based on the rule, style of top-down, and the other is based on the swarm intelligence, style of down-top. Some development directions of current mission planning technology research for the unmanned aerial vehicle swarm are analyzed. The summary has important reference significance for the comprehensive understanding of mission planning technology of the unmanned aerial vehicle swarm.

Key words: unmanned aerial vehicle swarm, mission planning, swarm intelligence, swarm behavior, research status

中图分类号:

贾高伟, 王建峰. 无人机集群任务规划方法研究综述[J]. 系统工程与电子技术, 2021, 43(1): 99-111.

Gaowei JIA, Jianfeng WANG. Research review of UAV swarm mission planning method[J]. Systems Engineering and Electronics, 2021, 43(1): 99-111.

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性能	无人机集群	多无人机
组成数量	多	较少
人工干预	少	多
协同等级	高	低
空间密度	大	小
任务类型	更多	有限
控制难度	难	易
平台特征	个体偏小、成本更低	通常为高端无人机
链路控制	无中心自组网	点对点、星状网

性能	基于逻辑与规则	基于集群智能涌现
基本架构	由上至下	由下至上
知识机理	人类认知	生物集群自然行为
知识形态	显示表达	隐式表达
行为样式	可编程行为	涌现式行为
规模效应	敏感	不敏感
数学模型	复杂建模	简单准则
控制范围	区域内全局控制	个体局部控制
任务样式	计划样式内复杂多变	受研究现状制约
人为干预	直接	间接
发展路线	单机-多机-集群	生物集群行为模仿与映射

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