Calibration of 3D lidars: A fully automatic and robust method for calibrating multiple 3D lidars using only point cloud data
Typ
Examensarbete för masterexamen
Program
Systems, control and mechatronics (MPSYS), MSc
Publicerad
2020
Författare
Langfjord Nordgård, Torgeir
Ravndal Skjølingstad, Olav
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
In order to use lidars for perception in autonomous vehicles, they must be properly
calibrated. Commonly used techniques for automatic calibration, such as iterative
closest point, often requires an accurate guess of the calibration parameters,
which is challenging to obtain. Additionally, these techniques are often dependent
on feature-extraction or designated calibration environments, which are highly
application-specific. We propose an alternative calibration algorithm for an arbitrary
number of lidars based on particle swarm optimization. Using our method, accurate
calibration parameters can be produced from extremely rough initial guesses, without
the aforementioned application-specific limitations. When tested on synthetic
data, the algorithm is shown to be superior to conventional methods. Additionally, a
method for allowing calibration during vehicle movement is explored and proposed.
Beskrivning
Ämne/nyckelord
lidar calibration , point clouds , stochastic optimization , voxel grid filter