{"title":"四旋翼无人机群中目标围护的自适应聚合算法","authors":"A. Bandala, R. R. Vicerra, E. Dadios","doi":"10.1109/HNICEM.2014.7016203","DOIUrl":null,"url":null,"abstract":"This paper presents aggregation behavior algorithm that will be applied for unmanned aerial vehicle quadrotors (QUAV). The most basic behavior for natural swarms is aggregation. Other swarm or social behaviors are derived from the aggregation behavior. Due to the concept of independence, each swarm members are required to collect themselves together to perform a certain task. However the swarm faces different environments thus this behavior is very complex to accomplish. This is the reason why the researchers developed this paper for multi robotic systems. Simulations were done to test the said algorithm and the researchers garnered the accuracy of 90.85%.","PeriodicalId":309548,"journal":{"name":"2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Adaptive aggregation algorithm for target enclosure implemented in quadrotor unmanned aerial vehicle (QUAV) swarm\",\"authors\":\"A. Bandala, R. R. Vicerra, E. Dadios\",\"doi\":\"10.1109/HNICEM.2014.7016203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents aggregation behavior algorithm that will be applied for unmanned aerial vehicle quadrotors (QUAV). The most basic behavior for natural swarms is aggregation. Other swarm or social behaviors are derived from the aggregation behavior. Due to the concept of independence, each swarm members are required to collect themselves together to perform a certain task. However the swarm faces different environments thus this behavior is very complex to accomplish. This is the reason why the researchers developed this paper for multi robotic systems. Simulations were done to test the said algorithm and the researchers garnered the accuracy of 90.85%.\",\"PeriodicalId\":309548,\"journal\":{\"name\":\"2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HNICEM.2014.7016203\",\"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 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM.2014.7016203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive aggregation algorithm for target enclosure implemented in quadrotor unmanned aerial vehicle (QUAV) swarm
This paper presents aggregation behavior algorithm that will be applied for unmanned aerial vehicle quadrotors (QUAV). The most basic behavior for natural swarms is aggregation. Other swarm or social behaviors are derived from the aggregation behavior. Due to the concept of independence, each swarm members are required to collect themselves together to perform a certain task. However the swarm faces different environments thus this behavior is very complex to accomplish. This is the reason why the researchers developed this paper for multi robotic systems. Simulations were done to test the said algorithm and the researchers garnered the accuracy of 90.85%.