  This paper presents a range-aided LiDAR-inertial multi-vehicle mapping system
(RaLI-Multi). Firstly, we design a multi-metric weights LiDAR-inertial odometry
by fusing observations from an inertial measurement unit (IMU) and a light
detection and ranging sensor (LiDAR). The degenerate level and direction are
evaluated by analyzing the distribution of normal vectors of feature point
clouds and are used to activate the degeneration correction module in which
range measurements correct the pose estimation from the degeneration direction.
We then design a multi-vehicle mapping system in which a centralized vehicle
receives local maps of each vehicle and range measurements between vehicles to
optimize a global pose graph. The global map is broadcast to other vehicles for
localization and mapping updates, and the centralized vehicle is dynamically
fungible. Finally, we provide three experiments to verify the effectiveness of
the proposed RaLI-Multi. The results show its superiority in degeneration
environments
