RTK-LIO: Tightly Coupled RTK/LiDAR/Inertial Navigation System Based on Optimization Approach

Global navigation satellite system real-time kinematic (GNSS-RTK) serves as a vital tool for providing absolute positioning for autonomous systems. However, its performance suffers considerable degradation in urban canyon environments due to the well-known challenges caused by multipath effects and non-line-of-sight (NLOS). Light detection and ranging (LiDAR)/inertial odometry (LIO) offers high-precision local pose estimation in structured urban settings, but it tends to accumulate drift over time. Recognizing their complementary strengths, this article proposes an adaptive integration of GNSS-RTK with LIO to achieve continuous and precise global positioning for autonomous systems in urban environments. The raw data are modeled and optimized within the framework of a factor graph. At the same time, double-difference (DD) carrier phase and ambiguity are added to the estimated states. Finally, RTK-LIO is evaluated on public datasets. It greatly exceeds the benchmarks [LiDAR-inertial-GNSS odometry (LIGO), GNSS/LiDAR/IMU odometry (GLIO), and real-time kinematic positioning (RTK)] in both accuracy and smoothness. To benefit the community, the implementation is open-sourced at http://gitee.com/bryantaoli/rtk-lio