{"title":"“自主与自适应控制”:受生物体自适应机制启发的协同群体控制算法","authors":"Masatsugu Ogawa, M. Emura, Masumi Ichien, M. Yano","doi":"10.1109/AUV.2016.7778710","DOIUrl":null,"url":null,"abstract":"Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental changes and events occurred in the real world. In general, it is difficult that an algorism reconciles the adaptability and optimization for a mission. In this context, we have been investigated the adaptive mechanism inspired by living organisms and realized a new control algorism called as “Autonomous and adaptive control”. This proposed algorism reconciles adaptability and ability of optimization for a mission of multi UxVs. In this paper, we apply the algorism to a use case of target tracking. It was confirmed that our algorism achieve most optimal operation in comparison of conventional algorisms with respect to energy consumption of the operation and the defense ability while keeping high detection ability. We also think that our algorism will be used for a lot of other use cases with multi UxVs.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"“Autonomous and Adaptive Control”: Collaborative swarm control algorism inspired by adaptive mechanism of living organisms\",\"authors\":\"Masatsugu Ogawa, M. Emura, Masumi Ichien, M. Yano\",\"doi\":\"10.1109/AUV.2016.7778710\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental changes and events occurred in the real world. In general, it is difficult that an algorism reconciles the adaptability and optimization for a mission. In this context, we have been investigated the adaptive mechanism inspired by living organisms and realized a new control algorism called as “Autonomous and adaptive control”. This proposed algorism reconciles adaptability and ability of optimization for a mission of multi UxVs. In this paper, we apply the algorism to a use case of target tracking. It was confirmed that our algorism achieve most optimal operation in comparison of conventional algorisms with respect to energy consumption of the operation and the defense ability while keeping high detection ability. We also think that our algorism will be used for a lot of other use cases with multi UxVs.\",\"PeriodicalId\":416057,\"journal\":{\"name\":\"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUV.2016.7778710\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUV.2016.7778710","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
“Autonomous and Adaptive Control”: Collaborative swarm control algorism inspired by adaptive mechanism of living organisms
Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental changes and events occurred in the real world. In general, it is difficult that an algorism reconciles the adaptability and optimization for a mission. In this context, we have been investigated the adaptive mechanism inspired by living organisms and realized a new control algorism called as “Autonomous and adaptive control”. This proposed algorism reconciles adaptability and ability of optimization for a mission of multi UxVs. In this paper, we apply the algorism to a use case of target tracking. It was confirmed that our algorism achieve most optimal operation in comparison of conventional algorisms with respect to energy consumption of the operation and the defense ability while keeping high detection ability. We also think that our algorism will be used for a lot of other use cases with multi UxVs.