  In this work, we present a detailed comparison of ten different 3D LiDAR
sensors, covering a range of manufacturers, models, and laser configurations,
for the tasks of mapping and vehicle localization, using as common reference
the Normal Distributions Transform (NDT) algorithm implemented in the
self-driving open source platform Autoware. LiDAR data used in this study is a
subset of our LiDAR Benchmarking and Reference (LIBRE) dataset, captured
independently from each sensor, from a vehicle driven on public urban roads
multiple times, at different times of the day. In this study, we analyze the
performance and characteristics of each LiDAR for the tasks of (1) 3D mapping
including an assessment map quality based on mean map entropy, and (2) 6-DOF
localization using a ground truth reference map.
