Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability

Identifying and mitigating sources of measurement error is a critical task in geomatics research and the geospatial industry as a whole. In pursuit of such error, accuracy assessments of lidar data have revealed a range bias in low-cost scanners. This phenomenon is a temporally correlated instabilit...

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Main Authors: Carter Kelly, Benjamin Wilkinson, Amr Abd-Elrahman, Orlando Cordero, H. Andrew Lassiter
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/14/17/4220
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author Carter Kelly
Benjamin Wilkinson
Amr Abd-Elrahman
Orlando Cordero
H. Andrew Lassiter
author_facet Carter Kelly
Benjamin Wilkinson
Amr Abd-Elrahman
Orlando Cordero
H. Andrew Lassiter
author_sort Carter Kelly
collection DOAJ
description Identifying and mitigating sources of measurement error is a critical task in geomatics research and the geospatial industry as a whole. In pursuit of such error, accuracy assessments of lidar data have revealed a range bias in low-cost scanners. This phenomenon is a temporally correlated instability in the lidar scanner where the measured distance between target and sensor changes over time while both are held stationary. This research presents an assessment of two low-cost lidar scanners, the Velodyne<sup>®</sup> HDL–32E and Livox<sup>®</sup> Mid–40, in which their temporal stability is analyzed and methods to mitigate systematic error are implemented. By immobilizing each scanner as it observes a stationary target surface over the course of multiple hours, trends in scanner precision are identified. Scanner accuracy is then determined using a terrestrial lidar scanner, the Riegl<sup>®</sup> VZ-400, to observe both subject scanner and target, and extracting the distances between scanner origin and observed surface. Patterns identified in each scanner’s distance measurements indicate temporal autocorrelation, and, by exploiting the high linear correlation between scanner internal temperature and measured distance in the HDL–32E, it is possible to mitigate the resulting error. Application of the proposed solution lowers the Velodyne<sup>®</sup> scanner’s measurement RMSE by over 60%, providing levels of measurement accuracy comparable to more expensive lidar systems.
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spelling doaj.art-afd686e5193946fcb801d0babbb02ffd2023-11-23T14:02:57ZengMDPI AGRemote Sensing2072-42922022-08-011417422010.3390/rs14174220Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal StabilityCarter Kelly0Benjamin Wilkinson1Amr Abd-Elrahman2Orlando Cordero3H. Andrew Lassiter4Geospatial Information Science Program, Department of Geography and Environmental Engineering, United States Military Academy (USMA), West Point, NY 10996, USAGeomatics Program, School of Forestry, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USAGeomatics Program, School of Forestry, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USAGeomatics Program, School of Forestry, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USAGeospatial Modeling and Applications (GMAP) Lab, School of Forestry, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USAIdentifying and mitigating sources of measurement error is a critical task in geomatics research and the geospatial industry as a whole. In pursuit of such error, accuracy assessments of lidar data have revealed a range bias in low-cost scanners. This phenomenon is a temporally correlated instability in the lidar scanner where the measured distance between target and sensor changes over time while both are held stationary. This research presents an assessment of two low-cost lidar scanners, the Velodyne<sup>®</sup> HDL–32E and Livox<sup>®</sup> Mid–40, in which their temporal stability is analyzed and methods to mitigate systematic error are implemented. By immobilizing each scanner as it observes a stationary target surface over the course of multiple hours, trends in scanner precision are identified. Scanner accuracy is then determined using a terrestrial lidar scanner, the Riegl<sup>®</sup> VZ-400, to observe both subject scanner and target, and extracting the distances between scanner origin and observed surface. Patterns identified in each scanner’s distance measurements indicate temporal autocorrelation, and, by exploiting the high linear correlation between scanner internal temperature and measured distance in the HDL–32E, it is possible to mitigate the resulting error. Application of the proposed solution lowers the Velodyne<sup>®</sup> scanner’s measurement RMSE by over 60%, providing levels of measurement accuracy comparable to more expensive lidar systems.https://www.mdpi.com/2072-4292/14/17/4220lidarUASaccuracy assessmentVelodyne HDL–32ELivox Mid–40range bias
spellingShingle Carter Kelly
Benjamin Wilkinson
Amr Abd-Elrahman
Orlando Cordero
H. Andrew Lassiter
Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
Remote Sensing
lidar
UAS
accuracy assessment
Velodyne HDL–32E
Livox Mid–40
range bias
title Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
title_full Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
title_fullStr Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
title_full_unstemmed Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
title_short Accuracy Assessment of Low-Cost Lidar Scanners: An Analysis of the Velodyne HDL–32E and Livox Mid–40’s Temporal Stability
title_sort accuracy assessment of low cost lidar scanners an analysis of the velodyne hdl 32e and livox mid 40 s temporal stability
topic lidar
UAS
accuracy assessment
Velodyne HDL–32E
Livox Mid–40
range bias
url https://www.mdpi.com/2072-4292/14/17/4220
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