基于EKF的移动机器人RFID定位系统研究

Study of Mobile-robot RFID Position System Based on Extended Kalman Filter

由于RFID读取器对标签的距离不可知,基于RFID的定位会产生固有误差。为了减小RFID定位系统的固有误差,研究了移动机器人融合RFID、超声波、电子罗盘和里程计自定位的方法,通过扩展卡尔曼滤波(extended Kalman filter,EKF)解决RFID定位在位姿更新之间的误差累积,提高定位的性能。通过Matlab仿真,试验结果表明该算法可行且有效。

RFID has been used to the robot position system with its capability of storing location and environment information, convenience of accessing to the information and its strong adaptability to the environment change. Because RFID reader could not get label＇s distance certainly ,RFID position system always causes inherent error. In order to reduce the inherent error of the system ,a self - localization method of mobile - robot combined with RFID, ultrasonic, electronic compass and speedometer was investigated. Error accumulation during RFID position changing was eliminated by extended Kalman filter. The method could therefore lower the position error and increase the performance of traditional RFID position. With Matlab simulation, the test results verified feasibility and validity of this arithmetic.