Abstract
A Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS)/Light Detection and Ranging (LiDAR)-Simultaneous Localization and Mapping (SLAM) integrated navigation system based on graph optimization is proposed and implemented in this paper. The navigation results are obtained by the information fusion of the GNSS position, Inertial Measurement Unit (IMU) preintegration result and the relative pose from the 3D probability map matching with graph optimizing. The sliding window method was adopted to ensure that the computational load of the graph optimization does not increase with time. Land vehicle tests were conducted, and the results show that the proposed GNSS/INS/LiDAR-SLAM integrated navigation system can effectively improve the navigation positioning accuracy compared to GNSS/INS and other current GNSS/INS/LiDAR methods. During the simulation of one-minute periods of GNSS outages, compared to the GNSS/INS integrated navigation system, the root mean square (RMS) of the position errors in the North and East directions of the proposed navigation system are reduced by approximately 82.2% and 79.6%, respectively, and the position error in the vertical direction and attitude errors are equivalent. Compared to the benchmark method of GNSS/INS/LiDAR-Google Cartographer, the RMS of the position errors in the North, East and vertical directions decrease by approximately 66.2%, 63.1% and 75.1%, respectively, and the RMS of the roll, pitch and yaw errors are reduced by approximately 89.5%, 92.9% and 88.5%, respectively. Furthermore, the relative position error during the GNSS outage periods is reduced to 0.26% of the travel distance for the proposed method. Therefore, the GNSS/INS/LiDAR-SLAM integrated navigation system proposed in this paper can effectively fuse the information of GNSS, IMU and LiDAR and can significantly mitigate the navigation error, especially for cases of GNSS signal attenuation or interruption.
Highlights
With the rapid development of autonomous driving and intelligent robots, the demand for navigation information with high data rates, high precision and all-weather features continues to increase, especially in complex urban environments
Among the various synthesized navigation techniques, the Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) integrated navigation system, which is dominated by the INS and supplemented by the GNSS, is the most popular
Considering the limitations of Cartographer and based on the Cartographer codes, a GNSS/INS/Light Detection and Ranging (LiDAR)-Simultaneous Localization and Mapping (SLAM) integrated navigation system is implemented in this paper based on graph optimization
Summary
With the rapid development of autonomous driving and intelligent robots, the demand for navigation information with high data rates, high precision and all-weather features continues to increase, especially in complex urban environments. Kukko [20] used the graph optimization method to combine the results of the GNSS/INS with a single-line LiDAR. Considering the limitations of Cartographer and based on the Cartographer codes, a GNSS/INS/LiDAR-SLAM integrated navigation system is implemented in this paper based on graph optimization. The MEMS-IMU mechanization is applied to predict the motion of the vehicle and provide the searching initial value for probability map scan matching with LiDAR in the front-end. In the back-end, the GNSS position provides the absolute position constraint, while the IMU preintegration [9,23] is applied to increase the motion constraints, and the LiDAR-SLAM scan matching provides the relative pose constraints. The GNSS/INS/LiDAR-SLAM integrated navigation system, an overview of which is shown, mainly is comprised of two parts: scan matching in the front-end and graph optimization in the back-end. 2.1.2C.1o.oCrdooinrdatine aFtreaFmreame TheTGheNGSSN/ISNSS/I/NLiSD/LAiRD-ASLRA-SMLAinMteginratetegdranteadvignaatvioignastiyosntesmysitnevmolivnevsomlvuelstimpluelctiopolredcinoaotredsinyastteems, andsyisntfeomrms,aatinodn ifnufsoiromnaitniondifffuesrieonnt icnoodridffienraetnet scyosoterdminsaitse nseyesdteemd.s iTshneeecdooedrd. iTnhateecsoyosrtdeimnasteand systems and transformation formula used in the GNSS/INS/LiDAR-SLAM integrated navigation system are given below
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