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During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance. Over a...
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Related Experiment Video

Updated: Dec 21, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
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Extrinsic LiDAR/Ground Calibration Method Using 3D Geometrical Plane-Based Estimation.

Mohammad Ali Zaiter1,2, Régis Lherbier1, Ghaleb Faour2

  • 1Laboratoire d'Informatique Signal et Image de la Côte d'Opale, Université du Littoral Côte d'Opale, LISIC, 59183 Dunkerque, France.

Sensors (Basel, Switzerland)
|May 21, 2020
PubMed
Summary

This study introduces an efficient extrinsic calibration method for LiDAR sensors, crucial for accurate ground object detection, especially at high inclination angles. The technique ensures precise 3D orientation and altitude estimation for reliable performance.

Keywords:
3D LiDARextrinsic calibrationlaser rangefinderroad surface object detection

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Area of Science:

  • Robotics and Autonomous Systems
  • Geospatial Engineering
  • Sensor Technology

Background:

  • Accurate extrinsic calibration of Light Detection and Ranging (LiDAR) sensors is critical for reliable ground surface object detection.
  • High angles of inclination present significant challenges for existing LiDAR calibration methods.
  • Ensuring the precision of LiDAR sensor parameters is vital across various applications, including autonomous navigation and environmental monitoring.

Purpose of the Study:

  • To propose and validate a novel extrinsic calibration method for scanning laser rangefinders.
  • To enhance the efficiency and accuracy of LiDAR calibration, particularly in challenging high-inclination configurations.
  • To improve the reliability of ground surface object detection through precise LiDAR sensor calibration.

Main Methods:

  • The method employs a geometrical ground plane-based estimation approach.
  • Key steps include fitting the ground plane, estimating extrinsic parameters (3D orientation angles and altitude), and optimizing these parameters.
  • Validation was performed using both numerical simulations and real-world data.

Main Results:

  • The proposed method demonstrates high precision and robustness against variations in LiDAR orientation and range accuracy.
  • The extrinsic calibration method shows stability and accuracy in challenging experimental setups.
  • Numerical simulations and real data confirmed the method's performance and effectiveness.

Conclusions:

  • The developed extrinsic calibration technique offers a stable and accurate solution for LiDAR sensors.
  • This method is particularly effective for LiDARs operating at high angles of inclination.
  • The validated approach contributes to improved ground surface object detection and overall system reliability.