Pixel-Level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments

By Chongjian Yuan, Xiyuan Liu, Xiaoping Hong, Fu Zhang. IEEE Robotics and Automation Letters, 2021

324 citations recorded by the source corpus.

In this letter, we present a novel method for automatic extrinsic calibration of high-resolution LiDARs and RGB cameras in targetless environments. Our approach does not require checkerboards but can achieve pixel-level accuracy by aligning natural edge features in the two sensors. On the theory level, we analyze the constraints imposed by edge features and the sensitivity of calibration accuracy with respect to edge distribution in the scene. On the implementation level, we carefully investigate the physical measuring principles of LiDARs and propose an efficient and accurate LiDAR edge extraction method based on point cloud voxel cutting and plane fitting. Due to the edges’ richness in natural scenes, we have carried out experiments in many indoor and outdoor scenes. The results show that this method has high robustness, accuracy, and consistency. It can promote the research and application of the fusion between LiDAR and camera. We have open sourced our code on GitHub1 to benefit the community.

Subfields: Aerospace Engineering, Environmental Engineering, Instrumentation

View Paper: https://www.semanticscholar.org/paper/4ebea79c8efa13714472ac6a952bd9adbea4539d

How researchers see this paper

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In Aerospace Engineering

  1. Fu Zhang
  2. Jiarong Lin
  3. Wei Xu

In Environmental Engineering

  1. Fu Zhang
  2. Jiarong Lin
  3. Wei Xu

In Instrumentation

  1. Jiarong Lin
  2. Fu Zhang

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