协同侦察中多无人机任务聚类与任务规划研究

Zhao Junwei, Zhao Jianjun
{"title":"协同侦察中多无人机任务聚类与任务规划研究","authors":"Zhao Junwei, Zhao Jianjun","doi":"10.1109/IHMSC.2014.196","DOIUrl":null,"url":null,"abstract":"For multi-UAV cooperative reconnaissance to enemy's multi-task points, because of multi-task, reasonable clustering is needed and the task clustering model should be established. In this paper, the task planning model is established according to task clustering of each UAV, and the sequence of task execution is determined. Reasonable task clustering optimization index is put forward. Task allocation is proposed based on improved K-means clustering algorithm of simulated annealing. The shortest path task planning is designed using the simulated annealing algorithm, which makes multi-UAV relatively balanced in the assignments, the task group in the group centralized distribution, inter-group distribution scattered and the total cruise time shortest. Simulation results show that the task clustering is well achieved and the optimum task planning program is obtained. The validity of the model and algorithm is verified and the algorithm has certain theoretical and practical value.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Study on Multi-UAV Task Clustering and Task Planning in Cooperative Reconnaissance\",\"authors\":\"Zhao Junwei, Zhao Jianjun\",\"doi\":\"10.1109/IHMSC.2014.196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For multi-UAV cooperative reconnaissance to enemy's multi-task points, because of multi-task, reasonable clustering is needed and the task clustering model should be established. In this paper, the task planning model is established according to task clustering of each UAV, and the sequence of task execution is determined. Reasonable task clustering optimization index is put forward. Task allocation is proposed based on improved K-means clustering algorithm of simulated annealing. The shortest path task planning is designed using the simulated annealing algorithm, which makes multi-UAV relatively balanced in the assignments, the task group in the group centralized distribution, inter-group distribution scattered and the total cruise time shortest. Simulation results show that the task clustering is well achieved and the optimum task planning program is obtained. The validity of the model and algorithm is verified and the algorithm has certain theoretical and practical value.\",\"PeriodicalId\":370654,\"journal\":{\"name\":\"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2014.196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2014.196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

摘要

多无人机协同侦察敌方多任务点,由于任务多,需要合理的聚类,建立任务聚类模型。本文根据每架无人机的任务聚类,建立任务规划模型,确定任务执行顺序。提出了合理的任务聚类优化指标。提出了一种基于改进的模拟退火k均值聚类算法的任务分配方法。采用模拟退火算法设计最短路径任务规划,使多架无人机的任务分配相对均衡,任务群内集中分布,群间分散分布,总巡航时间最短。仿真结果表明,该方法能很好地实现任务聚类,得到最优的任务规划方案。验证了模型和算法的有效性,该算法具有一定的理论和实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Multi-UAV Task Clustering and Task Planning in Cooperative Reconnaissance
For multi-UAV cooperative reconnaissance to enemy's multi-task points, because of multi-task, reasonable clustering is needed and the task clustering model should be established. In this paper, the task planning model is established according to task clustering of each UAV, and the sequence of task execution is determined. Reasonable task clustering optimization index is put forward. Task allocation is proposed based on improved K-means clustering algorithm of simulated annealing. The shortest path task planning is designed using the simulated annealing algorithm, which makes multi-UAV relatively balanced in the assignments, the task group in the group centralized distribution, inter-group distribution scattered and the total cruise time shortest. Simulation results show that the task clustering is well achieved and the optimum task planning program is obtained. The validity of the model and algorithm is verified and the algorithm has certain theoretical and practical value.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书