Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments

Xiyuan Liu, Fu Zhang Zhang*

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

41 Citations (Scopus)

Abstract

The integration of multiple solid state LiDARs could achieve similar performance as a spinning LiDAR, by focusing on the dedicated area of interests. However, due to their small FoV settings, it is either required to rely on external sensors or form FoV overlaps to calibrate the extrinsic parameters between multiple LiDAR units. To overcome such limitations, we develop a targetless calibration method, which creates FoV overlaps (hence co-visible features) through movements and constructs a factor graph to resolve the constraints between LiDAR poses and extrinsic parameters. By solving the formulated problem with graph optimization, our proposed method could calibrate the extrinsic of LiDARs with few or even no overlapped FoVs, meanwhile, produce a globally consistent point cloud map. Experiments on different sensor setups and scenes have demonstrated the accuracy and robustness of our proposed approach.

Original languageEnglish
Article number9361153
Pages (from-to)2036-2043
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume6
Issue number2
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Calibration and identification
  • localization
  • mapping

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