{"title":"协调联网无人飞行器进行持续区域拒止","authors":"Y. Liu, J. B. Cruz, A. Sparks","doi":"10.1109/CDC.2004.1429003","DOIUrl":null,"url":null,"abstract":"This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Coordinating networked uninhabited air vehicles for persistent area denial\",\"authors\":\"Y. Liu, J. B. Cruz, A. Sparks\",\"doi\":\"10.1109/CDC.2004.1429003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.\",\"PeriodicalId\":254457,\"journal\":{\"name\":\"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2004.1429003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2004.1429003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coordinating networked uninhabited air vehicles for persistent area denial
This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.