  We demonstrate a multi-lidar calibration framework for large mobile platforms
that jointly calibrate the extrinsic parameters of non-overlapping
Field-of-View (FoV) lidar sensors, without the need for any external
calibration aid. The method starts by estimating the pose of each lidar in its
corresponding sensor frame in between subsequent timestamps. Since the pose
estimates from the lidars are not necessarily synchronous, we first align the
poses using a Dual Quaternion (DQ) based Screw Linear Interpolation. Afterward,
a Hand-Eye based calibration problem is solved using the DQ-based formulation
to recover the extrinsics. Furthermore, we verify the extrinsics by matching
chosen lidar semantic features, obtained by projecting the lidar data into the
camera perspective after time alignment using vehicle kinematics. Experimental
results on the data collected from a Scania vehicle [$\sim$ 1 Km sequence]
demonstrate the ability of our approach to obtain better calibration parameters
than the provided vehicle CAD model calibration parameters. This setup can also
be scaled to any combination of multiple lidars.

Robotics