{"title":"Based on PSO algorithm multiple task assignments for cooperating UAVs","authors":"Wang Xinzeng, Ci Linlin, Lin Junshan, Yu Ning","doi":"10.1109/ICEIT.2010.5608449","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to multiple task assignments for cooperating unmanned aerial vehicles (UAVs).Aim at the problem of assigning cooperating UAVs to perform multiple task that includes identifying and attack, along with subsequent battle damage verification on multiple targets, the multiple task assignments model is built, It not only takes into account the requirements of the scenario such as task precedence and coordination, timing constraints, trajectories limitations, but also thinks the requirements of task for weapon kinds of UAV and capability of UAV and flyable trajectories, etc. The optimal solution of the multiple task assignments is an NP-hard problem. When some of the tasks must be accomplished at specified time and with specific vehicles and specific weapon, the problem becomes highly complex, and search for an optimum solution may be a very difficult task. The particle swarm optimization algorithm is improved and is used for solving multiple task assignments problem. We construct a double layer position vector spaces, it makes the particle of the particle swarm optimization algorithm correspond to the feasible solution of multiple task assignments problem. Simulations showing that it consistently and quickly provides good feasible solutions.","PeriodicalId":346498,"journal":{"name":"2010 International Conference on Educational and Information Technology","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Educational and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIT.2010.5608449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents a novel approach to multiple task assignments for cooperating unmanned aerial vehicles (UAVs).Aim at the problem of assigning cooperating UAVs to perform multiple task that includes identifying and attack, along with subsequent battle damage verification on multiple targets, the multiple task assignments model is built, It not only takes into account the requirements of the scenario such as task precedence and coordination, timing constraints, trajectories limitations, but also thinks the requirements of task for weapon kinds of UAV and capability of UAV and flyable trajectories, etc. The optimal solution of the multiple task assignments is an NP-hard problem. When some of the tasks must be accomplished at specified time and with specific vehicles and specific weapon, the problem becomes highly complex, and search for an optimum solution may be a very difficult task. The particle swarm optimization algorithm is improved and is used for solving multiple task assignments problem. We construct a double layer position vector spaces, it makes the particle of the particle swarm optimization algorithm correspond to the feasible solution of multiple task assignments problem. Simulations showing that it consistently and quickly provides good feasible solutions.