Localization of mobile robot based on multi-sensor fusion

In order to realize the precise positioning of mobile robot, the data information of multiple sensors needs to be collected by the localization system to enhance the state estimation ability of robot. Due to the need for accurate calibration and initialization of sensor groups, as well as the processing of measurement errors with different rates and delays, multi-sensor fusion still needs to solve many problems and faces many challenges. A method of multi-sensor fusion, which can analyze and screen the signal quality of sensors is proposed in this paper. Based on the extended Kalman filter, UWB data, IMU data and Lidar data are fused. By filtering and processing the sensor information, the impact of noise can be reduced. At the same time, the results of various sensor information fusion are closer to the actual results, and the mobile robot can be located.