{"title":"The development of hybrid methods in simple swarm robots for gas leak localization","authors":"Husnawati, Gita Fadila Fitriana, S. Nurmaini","doi":"10.1109/ICSIGSYS.2017.7967040","DOIUrl":null,"url":null,"abstract":"The olfactory system of swarm robot are needed to build reliable early gas leak detection, for decreasing the bad impact in the environment. This paper proposes hybrid methods related to locating the gas leak and identify the type of gas by using swarm robots. The propose hybrid methods combination with three algorithms and with three functions, such as the fuzzy logic system for swarm robot navigation, support vector machine (SVM) for gas identification, and particle swarm optimization (PSO) for route optimization. The result of this research shows the set of methods can be implemented to localize gas leak source at the indoor environment in a real experiment. This research is expected by using this method, the swarm robots have the ability to identify the source of the gas leak and localize the target in a short time without collision with the obstacle in the swarm environment.","PeriodicalId":212068,"journal":{"name":"2017 International Conference on Signals and Systems (ICSigSys)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Signals and Systems (ICSigSys)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIGSYS.2017.7967040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The olfactory system of swarm robot are needed to build reliable early gas leak detection, for decreasing the bad impact in the environment. This paper proposes hybrid methods related to locating the gas leak and identify the type of gas by using swarm robots. The propose hybrid methods combination with three algorithms and with three functions, such as the fuzzy logic system for swarm robot navigation, support vector machine (SVM) for gas identification, and particle swarm optimization (PSO) for route optimization. The result of this research shows the set of methods can be implemented to localize gas leak source at the indoor environment in a real experiment. This research is expected by using this method, the swarm robots have the ability to identify the source of the gas leak and localize the target in a short time without collision with the obstacle in the swarm environment.