{"title":"车辆机器人编队中相对定位的无线接收信号强度","authors":"Arturo Gil-Pinto, P. Fraisse, R. Zapata","doi":"10.1109/LARS.2006.334330","DOIUrl":null,"url":null,"abstract":"An integration of the wireless network signal strength data with the vehicle sensors information by means of a Kalman filter is proposed to estimated the relative position of each vehicle in a robot formation set. Vehicle sensors consist of wheel speed and steering angle, the WiFi data consist of reception signal strength (RSS) and the angle of the maximal RSS with respect to the robot orientation. A nonholonomic nonlinear model vehicle is considered, due to this nonlinearities a extended Kalman filter EKF is used. Simulation and experimental results of the proposed estimation strategy are presented","PeriodicalId":129005,"journal":{"name":"2006 IEEE 3rd Latin American Robotics Symposium","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Wireless Reception Signal Strength for Relative Positioning in a Vehicle Robot Formation\",\"authors\":\"Arturo Gil-Pinto, P. Fraisse, R. Zapata\",\"doi\":\"10.1109/LARS.2006.334330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An integration of the wireless network signal strength data with the vehicle sensors information by means of a Kalman filter is proposed to estimated the relative position of each vehicle in a robot formation set. Vehicle sensors consist of wheel speed and steering angle, the WiFi data consist of reception signal strength (RSS) and the angle of the maximal RSS with respect to the robot orientation. A nonholonomic nonlinear model vehicle is considered, due to this nonlinearities a extended Kalman filter EKF is used. Simulation and experimental results of the proposed estimation strategy are presented\",\"PeriodicalId\":129005,\"journal\":{\"name\":\"2006 IEEE 3rd Latin American Robotics Symposium\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE 3rd Latin American Robotics Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LARS.2006.334330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 3rd Latin American Robotics Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LARS.2006.334330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wireless Reception Signal Strength for Relative Positioning in a Vehicle Robot Formation
An integration of the wireless network signal strength data with the vehicle sensors information by means of a Kalman filter is proposed to estimated the relative position of each vehicle in a robot formation set. Vehicle sensors consist of wheel speed and steering angle, the WiFi data consist of reception signal strength (RSS) and the angle of the maximal RSS with respect to the robot orientation. A nonholonomic nonlinear model vehicle is considered, due to this nonlinearities a extended Kalman filter EKF is used. Simulation and experimental results of the proposed estimation strategy are presented
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