RTK-LIO: Tightly Coupled RTK/LiDAR/Inertial Navigation System Based on Optimization Approach
Rongtian Wang, Yuqi Zhang, Tao Li, Chao Wang, Qi Wu, Ling Pei, Wen‐An Zhang
Zhejiang University of Technology Shanghai Jiao Tong University
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摘要与影响
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 paper 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 is modeled and optimized within the framework of a factor graph. At the same time, double difference carrier phase and ambiguity are added to the estimated states. Finally, RTK-LIO is evaluated on public datasets. It greatly exceeds the benchmarks (LIGO, GLIO and RTK) in both accuracy and smoothness. To benefit the community, the implementation is open-sourced at https://gitee.com/bryantaoli/rtk-lio.
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工程Robotics and Sensor-Based Localization
Inertial Sensor and Navigation · Robotic Path Planning Algorithms
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