Continuous GNSS-RTK Aided by LiDAR/Inertial Odometry with Intelligent GNSS Selection in Urban Canyons

Accurate and globally referenced positioning is the key prerequisite for fully successful autonomous systems. Global Navigation Satellite System (GNSS) could provide global service in open areas. Unfortunately, under denes urban areas, which it typical systems to operate, performance of GNSS suffers from non-line-of-sight (NLOS) receptions multipath effects caused by signal reflection blockage surrounding buildings. Thus, will lead position measurements with terribly large errors outage. To facilitate long-term stable accurate navigation, this paper proposes a method continuous Real-time Kinematic (RTK) aided he 3D light detection ranging (LiDAR) /inertial odometry (LIO) intelligent selection canyons. The coarse-to-fine LIO keeps on generating locally motion estimation registered point cloud map. Inspired outstanding capability environmental description LiDAR, available GNSS-RTK environment detected as degree urbanization evaluated via sky-mask elevation angle calculation, be further integrated relative based factor graph optimization. Therefore, guaranteed local low-drift highly urbanized areas correction once “Available GNSS-RTK” obtained. experimental results canyon Hong Kong shows that proposed integration pipeline significantly improved comparison without selection.