  This paper presents a Light Detection and Ranging (LiDAR) data set that
targets complex urban environments. Urban environments with high-rise buildings
and congested traffic pose a significant challenge for many robotics
applications. The presented data set is unique in the sense it is able to
capture the genuine features of an urban environment (e.g. metropolitan areas,
large building complexes and underground parking lots). Data of two-dimensional
(2D) and threedimensional (3D) LiDAR, which are typical types of LiDAR sensors,
are provided in the data set. The two 16-ray 3D LiDARs are tilted on both sides
for maximal coverage. One 2D LiDAR faces backward while the other faces
forwards to collect data of roads and buildings, respectively. Raw sensor data
from Fiber Optic Gyro (FOG), Inertial Measurement Unit (IMU), and the Global
Positioning System (GPS) are presented in a file format for vehicle pose
estimation. The pose information of the vehicle estimated at 100 Hz is also
presented after applying the graph simultaneous localization and mapping (SLAM)
algorithm. For the convenience of development, the file player and data viewer
in Robot Operating System (ROS) environment were also released via the web
page. The full data sets are available at: http://irap.kaist.ac.kr/dataset. In
this website, 3D preview of each data set is provided using WebGL.
