  We present a robust system for state estimation that fuses measurements from
multiple lidars and inertial sensors with GNSS data. To initiate the method, we
use the prior GNSS pose information. We then perform incremental motion in
real-time, which produces robust motion estimates in a global frame by fusing
lidar and IMU signals with GNSS translation components using a factor graph
framework. We also propose methods to account for signal loss with a novel
synchronization and fusion mechanism. To validate our approach extensive tests
were carried out on data collected using Scania test vehicles (5 sequences for
a total of ~ 7 Km). From our evaluations, we show an average improvement of 61%
in relative translation and 42% rotational error compared to a state-of-the-art
estimator fusing a single lidar/inertial sensor pair.
