{"title":"基于模拟退火的无人机协同目标观测","authors":"Beulah Moses, L. Jain","doi":"10.1504/IJIDSS.2008.021970","DOIUrl":null,"url":null,"abstract":"Simulated Annealing (SA) is used to solve various combinatorial optimisation problems and local search problems. This paper deals with Cooperative Target Observation (CTO) by groups of Unmanned Aerial Vehicles (UAV). We propose a Modified SA algorithm for optimising the position of each of the UAVs to observe the maximum number of targets. CTO is a very good example of study of multi agent cooperation. We compare with Hill Climbing algorithm and Modified SA algorithm and find that the Modified SA algorithm is superior for almost all target speeds, UAV sensor ranges and various group sizes.","PeriodicalId":311979,"journal":{"name":"Int. J. Intell. Def. Support Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cooperative Target Observation of UAVs using Simulated Annealing\",\"authors\":\"Beulah Moses, L. Jain\",\"doi\":\"10.1504/IJIDSS.2008.021970\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Simulated Annealing (SA) is used to solve various combinatorial optimisation problems and local search problems. This paper deals with Cooperative Target Observation (CTO) by groups of Unmanned Aerial Vehicles (UAV). We propose a Modified SA algorithm for optimising the position of each of the UAVs to observe the maximum number of targets. CTO is a very good example of study of multi agent cooperation. We compare with Hill Climbing algorithm and Modified SA algorithm and find that the Modified SA algorithm is superior for almost all target speeds, UAV sensor ranges and various group sizes.\",\"PeriodicalId\":311979,\"journal\":{\"name\":\"Int. J. Intell. Def. Support Syst.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Intell. Def. Support Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJIDSS.2008.021970\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Intell. Def. Support Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJIDSS.2008.021970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cooperative Target Observation of UAVs using Simulated Annealing
Simulated Annealing (SA) is used to solve various combinatorial optimisation problems and local search problems. This paper deals with Cooperative Target Observation (CTO) by groups of Unmanned Aerial Vehicles (UAV). We propose a Modified SA algorithm for optimising the position of each of the UAVs to observe the maximum number of targets. CTO is a very good example of study of multi agent cooperation. We compare with Hill Climbing algorithm and Modified SA algorithm and find that the Modified SA algorithm is superior for almost all target speeds, UAV sensor ranges and various group sizes.
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