Next Article in Journal
Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management
Next Article in Special Issue
Detection of Interference Phase by Digital Computation of Quadrature Signals in Homodyne Laser Interferometry
Previous Article in Journal
Computational Design of a Carbon Nanotube Fluorofullerene Biosensor
Previous Article in Special Issue
Tree Height Growth Measurement with Single-Scan Airborne, Static Terrestrial and Mobile Laser Scanning
Sensors 2012, 12(10), 13736-13752; doi:10.3390/s121013736
Article

On-Site Sensor Recalibration of a Spinning Multi-Beam LiDAR System Using Automatically-Detected Planar Targets

*  and
Received: 3 August 2012; in revised form: 27 September 2012 / Accepted: 8 October 2012 / Published: 12 October 2012
(This article belongs to the Special Issue Laser Sensing and Imaging)
View Full-Text   |   Download PDF [1112 KB, uploaded 21 June 2014]   |   Browse Figures
Abstract: This paper presents a fully-automated method to establish a calibration dataset from on-site scans and recalibrate the intrinsic parameters of a spinning multi-beam 3-D scanner. The proposed method has been tested on a Velodyne HDL-64E S2 LiDAR system, which contains 64 rotating laser rangefinders. By time series analysis, we found that the collected range data have random measurement errors of around ±25 mm. In addition, the layered misalignment of scans among the rangefinders, which is identified as a systematic error, also increases the difficulty to accurately locate planar surfaces. We propose a temporal-spatial range data fusion algorithm, along with a robust RANSAC-based plane detection algorithm to address these issues. Furthermore, we formulate an alternative geometric interpretation of sensory data using linear parameters, which is advantageous for the calibration procedure. The linear representation allows the proposed method to be generalized to any LiDAR system that follows the rotating beam model. We also confirmed in this paper, that given effective calibration datasets, the pre-calibrated factory parameters can be further tuned to achieve significantly improved performance. After the optimization, the systematic error is noticeable lowered, and evaluation shows that the recalibrated parameters outperform the factory parameters with the RMS planar errors reduced by up to 49%.
Keywords: on-site calibration; LiDAR system; 3-D reconstruction; plane detection on-site calibration; LiDAR system; 3-D reconstruction; plane detection
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Chen, C.-Y.; Chien, H.-J. On-Site Sensor Recalibration of a Spinning Multi-Beam LiDAR System Using Automatically-Detected Planar Targets. Sensors 2012, 12, 13736-13752.

AMA Style

Chen C-Y, Chien H-J. On-Site Sensor Recalibration of a Spinning Multi-Beam LiDAR System Using Automatically-Detected Planar Targets. Sensors. 2012; 12(10):13736-13752.

Chicago/Turabian Style

Chen, Chia-Yen; Chien, Hsiang-Jen. 2012. "On-Site Sensor Recalibration of a Spinning Multi-Beam LiDAR System Using Automatically-Detected Planar Targets." Sensors 12, no. 10: 13736-13752.


Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert