An Integrated RTK/INS/Solid-State LiDAR Method for Large-Scale Vehicle Navigation in High-Mobility Scenarios

Jiahui Liu, Cheng Chi, Yingchao Xiao, Xin Zhang and Xingqun Zhan

Abstract:	Robust and accurate urban navigation is essential for autonomous driving. For long-time vehicle navigation, Global Navigation Satellite System (GNSS) is indispensable since it provides a low-cost absolute navigation solution, but suffers from signal interference and outages. In this context, LiDAR(Light detection and ranging)-Inertial Odometry (LIO) is an alternative local navigation technique that is robust under most urban scenarios, and the recent availability of low-cost solid-state LiDAR has further enhanced the appeal of LIO. Hence, this article proposes an integrated navigation scheme that combines GNSS RTK (Real-time Kinematic), INS (Inertial Navigation System), and solid-state LiDAR through factor graph optimization, thereby providing robust pose estimation. This word features various experiments conducted in large-scale outdoor environments, showcasing the effectiveness of the proposed method in overcoming GNSS signal blockages during long-term runs. Besides, the presence of GNSS naturally mitigates the accumulation of large-scale errors in the LIO system and improves pose maintenance in high-mobility scenarios where LiDAR is challenged.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	1942 - 1952
Cite this article:	Liu, Jiahui, Chi, Cheng, Xiao, Yingchao, Zhang, Xin, Zhan, Xingqun, "An Integrated RTK/INS/Solid-State LiDAR Method for Large-Scale Vehicle Navigation in High-Mobility Scenarios," Proceedings of the 36th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 1942-1952. https://doi.org/10.33012/2023.19338
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