Indoor Mobile robot positioning based on UWB And Low Cost IMU

Abstract

Positioning for indoor mobile robot cannot be solved by a single sensor. In this paper, a positioning system based on the fusion of various sensor data is designed. The system integrates the UWB positioning results with the low-cost MEMS inertial measurement unit positioning results in order to improve the positioning accuracy of the system. The system consists of two Kalman filters, the first of which is used to combine gyroscope angular velocity information with magnetometer angle to get an accurate heading angle. The second Kalman filter combines the positioning results calculated by IMU with the positioning results of UWB, and finally obtains accurate positioning results. The final experimental results show that the method is effective.