{"title":"自主移动机器人无线传感器定位与姿态跟踪系统","authors":"Juzhong Zhang, Shengjin Li, Gang Lu, Qi Zhou","doi":"10.1109/ICMA.2010.5589262","DOIUrl":null,"url":null,"abstract":"This paper brings forward a novel hardware structure system for localization and pose tracking of an Autonomous Mobile Robot (AMR). The system consists of a CPU and four Wireless Sensor Nodes (WSN), i.e. two ultrasonic transmitter nodes and two ultrasonic receiver nodes. Four ultrasonic time-of-flight (TOF) measurements together with the velocity information of an AMR are used to update the AMR's location and pose by utilizing the Extended Kalman Filtering (EKF) algorithm. In order to verify the concept, two experiment prototypes were built. The AMR moved along a beeline path and an arc path respectively, simultaneously the system calculated the locations and the poses in time. The results proved that the new structure system has high performance as well as simplicity, and provides an excellent solution for AMR on the field of localization and pose tracking over indoor environment.","PeriodicalId":145608,"journal":{"name":"2010 IEEE International Conference on Mechatronics and Automation","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A new wireless sensor localization and pose tracking system for an Autonomous Mobile Robot\",\"authors\":\"Juzhong Zhang, Shengjin Li, Gang Lu, Qi Zhou\",\"doi\":\"10.1109/ICMA.2010.5589262\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper brings forward a novel hardware structure system for localization and pose tracking of an Autonomous Mobile Robot (AMR). The system consists of a CPU and four Wireless Sensor Nodes (WSN), i.e. two ultrasonic transmitter nodes and two ultrasonic receiver nodes. Four ultrasonic time-of-flight (TOF) measurements together with the velocity information of an AMR are used to update the AMR's location and pose by utilizing the Extended Kalman Filtering (EKF) algorithm. In order to verify the concept, two experiment prototypes were built. The AMR moved along a beeline path and an arc path respectively, simultaneously the system calculated the locations and the poses in time. The results proved that the new structure system has high performance as well as simplicity, and provides an excellent solution for AMR on the field of localization and pose tracking over indoor environment.\",\"PeriodicalId\":145608,\"journal\":{\"name\":\"2010 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2010.5589262\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2010.5589262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new wireless sensor localization and pose tracking system for an Autonomous Mobile Robot
This paper brings forward a novel hardware structure system for localization and pose tracking of an Autonomous Mobile Robot (AMR). The system consists of a CPU and four Wireless Sensor Nodes (WSN), i.e. two ultrasonic transmitter nodes and two ultrasonic receiver nodes. Four ultrasonic time-of-flight (TOF) measurements together with the velocity information of an AMR are used to update the AMR's location and pose by utilizing the Extended Kalman Filtering (EKF) algorithm. In order to verify the concept, two experiment prototypes were built. The AMR moved along a beeline path and an arc path respectively, simultaneously the system calculated the locations and the poses in time. The results proved that the new structure system has high performance as well as simplicity, and provides an excellent solution for AMR on the field of localization and pose tracking over indoor environment.