Calibration of 3D lidars: A fully automatic and robust method for calibrating multiple 3D lidars using only point cloud data

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dc.contributor.authorLangfjord Nordgård, Torgeir
dc.contributor.authorRavndal Skjølingstad, Olav
dc.contributor.departmentChalmers tekniska högskola / Institutionen för mekanik och maritima vetenskapersv
dc.contributor.examinerForsberg, Peter
dc.contributor.supervisorBrown, Lars
dc.date.accessioned2020-06-21T11:52:19Z
dc.date.available2020-06-21T11:52:19Z
dc.date.issued2020sv
dc.date.submitted2019
dc.description.abstractIn 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.sv
dc.identifier.coursecodeMMSX30sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/300919
dc.language.isoengsv
dc.relation.ispartofseries2020:17sv
dc.setspec.uppsokTechnology
dc.subjectlidar calibrationsv
dc.subjectpoint cloudssv
dc.subjectstochastic optimizationsv
dc.subjectvoxel grid filtersv
dc.titleCalibration of 3D lidars: A fully automatic and robust method for calibrating multiple 3D lidars using only point cloud datasv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
local.programmeSystems, control and mechatronics (MPSYS), MSc
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