Research On Key Technology Of Indoor High Precision Positioning Based On UWB/LiDAR

With the development of computer technology and the limitation of indoor positioning,traditional positioning technology can not meet the increasing demand of indoor positioning.In recent years,SLAM technology has been regarded as one of the key technologies for indoor positioning and mapping.LiDAR is widely used in SLAM research because of its accurate and reliable measurement performance.However,in some scenarios with insufficient structural features,LiDAR SLAM based on point cloud information will degrade,resulting in inaccurate localization.Therefore,LiDAR SLAM needs to be supplemented by other sensors.The positioning based on UWB is not easily affected by the environmental characteristics,and can obtain centimeter-level positioning accuracy in the line-of-sight environment.However,in the non-line-of-sight environment,there will be problems such as abnormal ranging value and NLOS error,and there will be positioning deviation in the UWB positioning in this environment.In this paper,aiming at the problem of inaccurate localization of LiDAR SLAM in degraded environment and NLOS ranging error in non-line-length environment,UWB and LiDAR sensors are fused to process sensor data respectively,and then the information provided by sensors is used to provide constraints for localization.The aim is to improve the positioning accuracy,robustness and reliability of indoor positioning system in complex environment.In this paper,indoor positioning method based on UWB/LiDAR combination will be studied.The main work is as follows:(1)In view of the existence of discrete points and miscellaneous points in the original point cloud data,the combined filter is used for processing.In view of the existence of motion distortion in LiDAR,the hypothesis based on uniform motion model is removed to improve the quality of the original point cloud of LiDAR.A detailed LiDAR front-end matching process is presented,and the degradation direction and degree of LiDAR SLAM are judged based on disturbance model.(2)In the non-line-of-sight environment,UWB data have problems such as ranging outliers and NLOS errors.The adaptive robust Kalman filter method of UWB ranging is used to reduce the influence of NLOS ranging errors and gross errors in the ranging information,and the ranging outliers in the ranging information are smoothen,which is verified by experiments.This method can obtain relatively smooth UWB ranging information,and use the reconstructed ranging value to estimate the system state optimally.(3)Considering that it is difficult for a single sensor to achieve high-precision positioning in a complex indoor environment,this paper proposes a UWB/LiDAR combined positioning model based on EKF to achieve effective fusion of UWB data and LiDAR data.(4)UWB/LiDAR combined positioning platform was built,and experiments were carried out in indoor degradation environment and indoor non-line-of sight environment.Experimental results show that compared with the single sensor model,UWB/LiDAR combined positioning method can effectively improve the positioning accuracy in indoor degradation environment and non-line-of sight environment,and improve the robustness of the system.The sub-meter positioning accuracy is achieved.The paper has 45 figures,4 tables and 88 references.