IC-GLI: a real-time, INS-centric GNSS-LiDAR-IMU localization system for intelligent vehicles

摘要

Abstract The integration of multiple sensors plays a vital role in achieving accurate vehicle positioning. However, light detection and ranging (LIDAR) and global navigation satellite system (GNSS) are susceptible to environmental effects, unlike inertial navigation system (INS), which remains unaffected by external factors. To enhance the precise positioning of intelligent vehicles in diverse environments and maximize the use of inertial measurement unit (IMU) data, this study presents a LIDAR, IMU, and GNSS-based positioning method centered around INS. The proposed method employs an IMU pre-integration model that includes the Earth’s rotation and utilizes a factor graph optimization framework to fuse the measurement data from LIDAR, IMU, and GNSS. By assigning appropriate weights to the residuals and dynamically adjusting the contributions of each sensor based on the prevailing environmental conditions, the optimal localization results are obtained through the solution of the maximum a posteriori estimate and the update of the INS state. Finally, the proposed system’s localization performance is validated using intelligent vehicles in the Robot Operating System framework. The results demonstrate that the system achieves high accuracy and robustness across various environments.