Abstract
Mapping is an essential task in mobile robotics. To
fulfil advanced navigation and manipulation tasks a
3D representation of the environment is
required. Applying stereo cameras or Time-of-flight
cameras (TOF cameras) are one way to archive this
requirement. Unfortunately, they suffer from
drawbacks which makes it difficult to map
properly. Therefore, costly 3D laser scanners are
applied. An inexpensive way to build a 3D
representation is to use a 2D laser scanner and
rotate the scan plane around an additional axis. A
3D point cloud acquired with such a custom device
consists of multiple 2D line scans. Therefore the
scanner pose of each line scan need to be determined
as well as parameters resulting from a calibration
to generate a 3D point cloud. Using external sensor
systems are a common method to determine these
calibration parameters. This is costly and difficult
when the robot needs to be calibrated outside the
lab. Thus, this work presents a calibration method
applied on a rotating 2D laser scanner. It uses a
hardware setup to identify the required parameters
for calibration. This hardware setup is light,
small, and easy to transport. Hence, an out of lab
calibration is possible. Additional a theoretical
model was created to test the algorithm and analyse
impact of the scanner accuracy. The hardware
components of the 3D scanner system are an HOKUYO
UTM-30LX-EW 2D laser scanner, a Dynamixel
servo-motor, and a control unit. The calibration
system consists of an hemisphere. In the inner of
the hemisphere a circular plate is mounted. The
algorithm needs to be provided with a dataset of a
single rotation from the laser scanner. To achieve a
proper calibration result the scanner needs to be
located in the middle of the hemisphere. By means of
geometric formulas the algorithms determine the
individual deviations of the placed laser
scanner. In order to minimize errors, the algorithm
solves the formulas in an iterative process. First,
the calibration algorithm was tested with an ideal
hemisphere model created in Matlab. Second, laser
scanner was mounted differently, the scanner
position and the rotation axis was modified. In
doing so, every deviation, was compared with the
algorithm results. Several measurement settings were
tested repeatedly with the 3D scanner system and the
calibration system. The results show that the length
accuracy of the laser scanner is most critical. It
influences the required size of the hemisphere and
the calibration accuracy.
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