{"title":"工业环境下的飞行时间无线室内导航系统","authors":"Maurizio Rea, Héctor Cordobés, D. Giustiniano","doi":"10.1145/3349623.3355476","DOIUrl":null,"url":null,"abstract":"We introduce TWINS, Time-of-flight based Wireless Indoor Navigation System, that estimates in near real-time the position of commercial off-the-shelf (COTS) devices equipped with WiFi. TWINS uses COTS WiFi Access Points (APs) and it does not require access to any inertial sensors on the mobile devices. We study the performance of TWINS in a harsh environment, strongly affected by the presence of metallic objects. The scenario can be considered representative of an industrial indoor environment with open spaces surrounded by metal obstacles. We experimentally show that our system can localize four mobile robots tracked together, with median error between 1.8 and 3.8 m.","PeriodicalId":403596,"journal":{"name":"Proceedings of the 13th International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Time-of-flight Wireless Indoor Navigation System for Industrial Environment\",\"authors\":\"Maurizio Rea, Héctor Cordobés, D. Giustiniano\",\"doi\":\"10.1145/3349623.3355476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce TWINS, Time-of-flight based Wireless Indoor Navigation System, that estimates in near real-time the position of commercial off-the-shelf (COTS) devices equipped with WiFi. TWINS uses COTS WiFi Access Points (APs) and it does not require access to any inertial sensors on the mobile devices. We study the performance of TWINS in a harsh environment, strongly affected by the presence of metallic objects. The scenario can be considered representative of an industrial indoor environment with open spaces surrounded by metal obstacles. We experimentally show that our system can localize four mobile robots tracked together, with median error between 1.8 and 3.8 m.\",\"PeriodicalId\":403596,\"journal\":{\"name\":\"Proceedings of the 13th International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3349623.3355476\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3349623.3355476","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time-of-flight Wireless Indoor Navigation System for Industrial Environment
We introduce TWINS, Time-of-flight based Wireless Indoor Navigation System, that estimates in near real-time the position of commercial off-the-shelf (COTS) devices equipped with WiFi. TWINS uses COTS WiFi Access Points (APs) and it does not require access to any inertial sensors on the mobile devices. We study the performance of TWINS in a harsh environment, strongly affected by the presence of metallic objects. The scenario can be considered representative of an industrial indoor environment with open spaces surrounded by metal obstacles. We experimentally show that our system can localize four mobile robots tracked together, with median error between 1.8 and 3.8 m.