  Mobile robots equipped with multiple light detection and ranging (LiDARs) and
capable of recognizing their surroundings are increasing due to the
minitualization and cost reduction of LiDAR. This paper proposes a target-less
extrinsic calibration method of multiple LiDARs with non-overlapping field of
view (FoV). The proposed method uses accumulated point clouds of floor plane
and objects while in motion. It enables accurate calibration with challenging
configuration of LiDARs that directed towards the floor plane, caused by biased
feature values. Additionally, the method includes a noise removal module that
considers the scanning pattern to address bleeding points, which are noises of
significant source of error in point cloud alignment using high-density LiDARs.
Evaluations through simulation demonstrate that the proposed method achieved
higher accuracy extrinsic calibration with two and four LiDARs than
conventional methods, regardless type of objects. Furthermore, the experiments
using a real mobile robot has shown that our proposed noise removal module can
eliminate noise more precisely than conventional methods, and the estimated
extrinsic parameters have successfully created consistent 3D maps.
