[1]齐小刚,李博,范英盛,等.多约束下多无人机的任务规划研究综述[J].智能系统学报,2020,15(2):204-217.[doi:10.11992/tis.201811018]
QI Xiaogang,LI Bo,FAN Yingsheng,et al.A survey of mission planning on UAVs systems based on multiple constraints[J].CAAI Transactions on Intelligent Systems,2020,15(2):204-217.[doi:10.11992/tis.201811018]
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QI Xiaogang,LI Bo,FAN Yingsheng,et al.A survey of mission planning on UAVs systems based on multiple constraints[J].CAAI Transactions on Intelligent Systems,2020,15(2):204-217.[doi:10.11992/tis.201811018]
多约束下多无人机的任务规划研究综述
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
15
期数:
2020年第2期
页码:
204-217
栏目:
综述
出版日期:
2020-03-05
- Title:
- A survey of mission planning on UAVs systems based on multiple constraints
- Keywords:
- unmanned aerial vehicle; mission planning; task assignment; path planning; heuristic algorithm; intelligence optimization algorithm; smoothing; flyable
- 分类号:
- TP393
- 摘要:
- 高度信息化的发展使得无人机作战优势凸显。准确的无人机任务规划技术是完成给定任务的重要保障。任务分配、路径规划是构成无人机任务规划技术的两个核心部分。基于该技术，首先讨论了无人机任务规划的发展状况、分类标准、体系结构。其次，分别详细介绍了影响任务分配、路径规划的重要指标，如分类标准、约束指标、相应模型、代表算法、评价指标等，然后，分别分析对比求解任务分配的启发式算法、数学规划方法、随机智能优化算法的优缺点和求解路径规划的数学规划方法、人工势场法、基于图形学法、智能优化算法的优缺点；最后，总结了无人机任务规划存在的开放性问题、未来发展方向和研究重点。
- Abstract:
- Depending on the highly developed information technology, unmanned aerial vehicles (UAVs) have shown unprecedented advantages in combat. Accurate mission planning technique for UAVs provides an important guarantee for completing a given mission. Task assignment and path planning are the two core components of the mission planning technology for UAVs. Based on this technology, first, the development status, classification standards, and architecture of the mission planning for UAVs are discussed. Second, the important indicators, which affect task assignment and path planning are described in detail; they include classification criteria, constraint indicator, corresponding model, representative algorithm, and evaluation indicator. Then, the strength and weakness of the algorithms for solving tasks are compared, such as heuristic algorithm, mathematical programming method, and stochastic intelligent optimization algorithm. Similarly, for the path planning problem, the advantages and disadvantages of its algorithms, which include mathematical programming method, artificial potential field method, graphic-based method, and intelligent optimization algorithm, are also analyzed. Finally, open problems, the future work, and the research focus in UAVs mission planning are summarized.
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备注/Memo
收稿日期:2018-11-24。
基金项目:国家自然科学基金项目(61877067，61572435)；教育部-中国移动联合基金项目(MCM20170103)；西安市科技创新项目(201805029YD7CG13-6)；宁波市自然科学基金项目(2016A610035，2017A610119)
作者简介:齐小刚，教授，博士生导师，主要研究方向为复杂系统建模与仿真、网络算法设计与应用。申请专利47项(授权19项)，登记软件著作权4项。发表学术论文100余篇;李博，硕士研究生，主要研究方向为网络协同定位与任务规划;范英盛，博士研究生，主要研究方向为移动网络协同定位。
通讯作者:李博.E-mail:libo202017@163.com
更新日期/Last Update:
1900-01-01