  Accurate and robust extrinsic calibration is necessary for deploying
autonomous systems which need multiple sensors for perception. In this paper,
we present a robust system for real-time extrinsic calibration of multiple
lidars in vehicle base frame without the need for any fiducial markers or
features. We base our approach on matching absolute GNSS and estimated lidar
poses in real-time. Comparing rotation components allows us to improve the
robustness of the solution than traditional least-square approach comparing
translation components only. Additionally, instead of comparing all
corresponding poses, we select poses comprising maximum mutual information
based on our novel observability criteria. This allows us to identify a subset
of the poses helpful for real-time calibration. We also provide stopping
criteria for ensuring calibration completion. To validate our approach
extensive tests were carried out on data collected using Scania test vehicles
(7 sequences for a total of ~ 6.5 Km). The results presented in this paper show
that our approach is able to accurately determine the extrinsic calibration for
various combinations of sensor setups.
