A Novel LiDAR Sensor Alignment Inspection System for Automobile Productions Using 1-D Photodetector Arrays
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The primary purpose of ADAS sensors is to improve the safety of passengers and the vehicle itself, which is the primary justification for developing AVs.
“The primary purpose of these sensors is to improve the safety of passengers and the vehicle itself, which is the primary justification for developing AVs [10].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [10]
Cites
2013 IEEE International Conference on Robotics and Automation
(2013) · doi:10.1109/icra19839.2013 · Cited by 2,025 · see citing works
Extrinsic calibration of a camera and laser range finder (improves camera calibration)
Zhang, Q., & Pless, R. B. (2005) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2004.1389752 · Cited by 697 · see citing works
Automatic camera and range sensor calibration using a single shot
Geiger, A., Moosmann, F., Car, O., & Schuster, B. (2012) · IEEE International Conference on Robotics and Automation · doi:10.1109/icra.2012.6224570 · Cited by 669 · see citing works
2006 IEEE Intelligent Transportation Systems Conference
(2006) · doi:10.1109/itsc10413.2006 · Cited by 580 · see citing works
Rançon, F., Bombrun, L., Keresztes, B., & Germain, C. (2018) · Remote Sensing · doi:10.3390/rs11010001 · Cited by 287 · see citing works
A Simple Algorithm for Fitting a Gaussian Function [DSP Tips and Tricks]
Guo, H. (2011) · IEEE Signal Processing Magazine · doi:10.1109/msp.2011.941846 · Cited by 242 · see citing works
Static Calibration and Analysis of the Velodyne HDL-64E S2 for High Accuracy Mobile Scanning
Glennie, C., & Lichti, D. D. (2010) · Remote Sensing · doi:10.3390/rs2061610 · Cited by 191 · see citing works
RT3D: Real-Time 3-D Vehicle Detection in LiDAR Point Cloud for Autonomous Driving
Zeng, Y., Hu, Y., Liu, S., Ye, J., Han, Y., Li, X., & Sun, N. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2852843 · Cited by 183 · see citing works
Accurate Calibration of LiDAR-Camera Systems Using Ordinary Boxes
Pusztai, Z., & Hajder, L. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.53 · Cited by 182 · see citing works
Mirzaei, F. M., Kottas, D. G., & Roumeliotis, S. I. (2012) · The International Journal of Robotics Research · doi:10.1177/0278364911435689 · Cited by 161 · see citing works
3D LIDAR-Camera Extrinsic Calibration Using an Arbitrary Trihedron
Gong, X., Lin, Y., & Liu, J. (2013) · Sensors · doi:10.3390/s130201902 · Cited by 153 · see citing works
Extrinsic calibration between a multi-layer lidar and a camera
Rodríguez, S., Frémont, V., & Bonnifait, P. (2008) · IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) · doi:10.1109/mfi.2008.4648067 · Cited by 142 · see citing works
LIDAR obstacle warning and avoidance system for unmanned aerial vehicle sense-and-avoid
Ramasamy, S., Sabatini, R., Gardi, A., & Liu, J. (2016) · Aerospace Science and Technology · doi:10.1016/j.ast.2016.05.020 · Cited by 132 · see citing works
Verma, S., Berrío, J. S., Worrall, S., & Nebot, E. (2019) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2019.8917108 · Cited by 116 · see citing works
Robust Vision-Based Relative-Localization Approach Using an RGB-Depth Camera and LiDAR Sensor Fusion
Song, H., Choi, W.-S., & Kim, H. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2521346 · Cited by 113 · see citing works
Self-citationA Lidar-Based Decision-Making Method for Road Boundary Detection Using Multiple Kalman Filters
Kang, Y., Roh, C.-W., Suh, S., & Song, B. (2012) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2012.2185013 · Cited by 110 · see citing works
LIDAR Velodyne HDL-64E Calibration Using Pattern Planes
Atanacio-Jiménez, G., González‐Barbosa, J., Hurtado‐Ramos, J. B., Ornelas-Rodríguez, F.-J., Jiménez‐Hernández, H., Garcia-Ramírez, T., & González-Barbosa, R. (2011) · International Journal of Advanced Robotic Systems · doi:10.5772/50900 · Cited by 110 · see citing works
Calibration of a rotating multi-beam lidar
Muhammad, N., & Lacroix, S. (2010) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2010.5651382 · Cited by 101 · see citing works
Map-Based Localization Method for Autonomous Vehicles Using 3D-LIDAR
Wang, L., Zhang, Y., & Wang, J. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.046 · Cited by 100 · see citing works
Alternative Methodologies for LiDAR System Calibration
Habib, A. F., Bang, K., Kersting, A. P., & Chow, J. (2010) · Remote Sensing · doi:10.3390/rs2030874 · Cited by 87 · see citing works
LiDAR-Camera Calibration Under Arbitrary Configurations: Observability and Methods
Fu, B., Wang, Y., Ding, X., Jiao, Y., Tang, L., & Xiong, R. (2019) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2019.2931526 · Cited by 75 · see citing works
Automatic Calibration of a Range Sensor and Camera System
Alismail, H., Baker, L. D., & Browning, B. (2012) · doi:10.1109/3dimpvt.2012.52 · Cited by 67 · see citing works
Pixels and 3-D Points Alignment Method for the Fusion of Camera and LiDAR Data
Xie, S., Yang, D., Jiang, K., & Zhong, Y. (2018) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2018.2879705 · Cited by 67 · see citing works
Error modeling and calibration of exteroceptive sensors for accurate mapping applications
Underwood, J., Hill, A. J., Peynot, T., & Scheding, S. (2009) · Journal of Field Robotics · doi:10.1002/rob.20315 · Cited by 65 · see citing works
Bolkas, D., & Martínez, A. (2017) · Journal of Applied Geodesy · doi:10.1515/jag-2017-0034 · Cited by 63 · see citing works
Optimal Extrinsic Calibration Between a Stereoscopic System and a LIDAR
Li, Y., Ruichek, Y., & Cappelle, C. (2013) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2013.2258241 · Cited by 61 · see citing works
Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping
Laconte, J., Deschenes, S.-P., Labussière, M., & Pomerleau, F. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8793671 · Cited by 47 · see citing works
Kim, Y., Kim, Y., Jung, Y., Jang, I. G., Kim, Y., Kim, S., & Kwak, B. (2012) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2012.2200225 · Cited by 42 · see citing works
Self-citationFuada, S., Putra, A. P., Aska, Y., & Adiono, T. (2016) · International Conference on Information Technology, Computer, and Electrical Engineering · doi:10.1109/icitacee.2016.7892405 · Cited by 42 · see citing works
Three-Dimensional Cooperative Mapping for Connected and Automated Vehicles
Zhang, Y., Chen, L. F., Xuanyuan, Z., & Tian, W. (2019) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2019.2931521 · Cited by 37 · see citing works
Extrinsic calibration of a camera-LIDAR multi sensor system using a planar chessboard
Kim, E.-S., & Park, S.-Y. (2019) · International Conference on Ubiquitous and Future Networks · doi:10.1109/icufn.2019.8806057 · Cited by 35 · see citing works
Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features
Hillemann, M., Martin Weinmann, A., Mueller, M., & Jutzi, B. (2019) · Remote Sensing · doi:10.3390/rs11161955 · Cited by 33 · see citing works
Heinz, E., Eling, C., Wieland, M., Klingbeil, L., & Kuhlmann, H. (2015) · Journal of Applied Geodesy · doi:10.1515/jag-2015-0011 · Cited by 29 · see citing works
Kim, Y.-K., Kim, K.-S., & Kim, S. (2015) · IEEE transactions on industrial electronics (1982. Print) · doi:10.1109/tie.2015.2410261 · Cited by 28 · see citing works
Self-citationHeinz, E., Holst, C., Kuhlmann, H., & Klingbeil, L. (2020) · Remote Sensing · doi:10.3390/rs12030555 · Cited by 24 · see citing works
Automatic Data Selection and Boresight Adjustment of LiDAR Systems
Keyetieu, R., & Seube, N. (2019) · Remote Sensing · doi:10.3390/rs11091087 · Cited by 20 · see citing works
Pozo-Antonio, J. S., Puente, I., Pereira, M. F. C., & Rocha, C. S. A. (2019) · Measurement · doi:10.1016/j.measurement.2019.03.066 · Cited by 19 · see citing works
Docking Design of Self-Reconfigurable Robot
Fei, Y. (2011) · International Journal of Advanced Robotic Systems · doi:10.5772/45709 · Cited by 18 · see citing works
Neupane, S. R., & Gharaibeh, N. G. (2018) · Measurement · doi:10.1016/j.measurement.2018.09.015 · Cited by 18 · see citing works
Unsupervised Extrinsic Parameters Calibration for Multi-beam LIDARs
Zhu, Z., & Liu, J. (2013) · International Conference on Computer Science and Electronics Engineering (ICCSEE) · doi:10.2991/iccsee.2013.278 · Cited by 14 · see citing works
Extrinsic self-calibration of an operational mobile LiDAR system
Diehm, A. L., Gehrung, J., Hebel, M., & Arens, M. (2020) · doi:10.1117/12.2556476 · Cited by 13 · see citing works
Accurate Alignment Inspection System for Low-Resolution Automotive LiDAR
Oh, S., You, J.-H., Eskandarian, A., & Kim, Y. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3049091 · Cited by 12 · see citing works
Self-citationA NEW RELIABLE BORESIGHT CALIBRATION METHOD FOR MOBILE LASER SCANNING APPLICATIONS
Scouarnec, R. L., Touzé, T., Lacambre, J. B., & Seube, N. (2014) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprsarchives-xl-3-w1-67-2014 · Cited by 11 · see citing works
3D LiDAR Extrinsic Calibration Method using Ground Plane Model Estimation
Zaiter, M. A., Lherbier, R., Faour, G., Bazzi, O., & Noyer, J.-C. (2019) · International Conference on Connected Vehicles and Expo · doi:10.1109/iccve45908.2019.8964949 · Cited by 11 · see citing works
Kim, Y., Jang, I. G., Kim, K., & Kim, S. (2014) · Review of Scientific Instruments · doi:10.1063/1.4861915 · Cited by 10 · see citing works
Self-citationAERIAL-TRIANGULATION AIDED BORESIGHT CALIBRATION FOR A LOW-COST UAV-LIDAR SYSTEM
Li, J., Yang, B., Chen, C., Wu, W., & Zhang, L. (2020) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-v-1-2020-245-2020 · Cited by 8 · see citing works
Hillemann, M., Jochen Meidow, A., & Jutzi, B. (2019) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlii-2-w16-119-2019 · Cited by 5 · see citing works
Kim, Y., & Kim, K.-S. (2014) · Review of Scientific Instruments · doi:10.1063/1.4897493 · Cited by 4 · see citing works
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Flagged first, then by citations
4 of the 53 references couldn’t be matched to a known paper.
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Raouf, I., Khan, A., Khalid, S., Sohail, M., Azad, M. M., & Kim, H. S. (2022) · Mathematics · doi:10.3390/math10183233 · Cited by 41 · see citing works
Core‐Shell Micro‐ and Nano‐Structures for The Modification of Light‐Surface Interactions
Yeo, R. J., Yeo, J. C. C., Tan, S. Y., Sng, A., Tomczak, N., Muiruri, J. K., Wang, S., Wang, P., Thitsartarn, W., Wang, F., et al. (2023) · Advanced Optical Materials · doi:10.1002/adom.202301955 · Cited by 31 · see citing works
Li, X., Bi, T., Wang, Z., Xu, L., & He, Y. (2022) · Measurement · doi:10.1016/j.measurement.2022.111479 · Cited by 24 · see citing works
Progress in Organic Photodiodes through Physical Process Insights
Chandran, H. T., Yan, C., & Li, G. (2022) · Advanced Energy and Sustainability Research · doi:10.1002/aesr.202200002 · Cited by 22 · see citing works
Liu, H.-Y., Wu, N.-Z., Wu, Y.-T., Chen, W.-H., & Chiu, N.-E. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3342739 · Cited by 22 · see citing works
Kim, S., Seo, J., Park, T., & Yoo, H. (2022) · Advanced Electronic Materials · doi:10.1002/aelm.202200752 · Cited by 12 · see citing works
Turned Surface Monitoring Using a Confocal Sensor and the Tool Wear Process Optimization
Jurko, J., Miškiv-Pavlík, M., Husár, J., & Michalík, P. (2022) · Processes · doi:10.3390/pr10122599 · Cited by 10 · see citing works
Li, X., Bi, T., & Xu, L. (2024) · Measurement · doi:10.1016/j.measurement.2024.114351 · Cited by 9 · see citing works
Kathmann, T., Reh, D., & Arlinghaus, J. C. (2022) · Advances in Industrial and Manufacturing Engineering · doi:10.1016/j.aime.2022.100111 · Cited by 8 · see citing works
Zhao, R., Huang, J., Liu, M., Tan, F., Zhang, P., Chen, Z., Yao, X., & Li, S. (2023) · Nanotechnology · doi:10.1088/1361-6528/acbcda · Cited by 8 · see citing works
Automatic Inspection System for Automotive LiDAR Alignment Using a Cubic Target
Song, H., You, J.-H., Park, J.-E., Eskandarian, A., & Kim, Y. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3133008 · Cited by 7 · see citing works
Self-citationJurko, J., Miškiv-Pavlík, M., Hladký, V., Lazorík, P., Michalík, P., & Petruška, I. (2022) · Applied Sciences · doi:10.3390/app12105266 · Cited by 5 · see citing works
Automatic One-Shot LiDAR Alignment Inspection System Using NIR Camera
Song, H., & Kim, Y. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3245219 · Cited by 5 · see citing works
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Song, H., Park, J.-E., Ahn, C.-M., & Kim, Y. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3565714 · Cited by 3 · see citing works
Self-citationWu, L., Cao, Q., Troyan, E., Zhang, X., Stsiapanau, A., Li, J., & Sun, X. W. (2025) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.5c00807 · Cited by 3 · see citing works
Liu, L., Tian, Y., Yu, J., & Yao, H. (2024) · Surfaces and Interfaces · doi:10.1016/j.surfin.2024.105421 · Cited by 2 · see citing works
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Ge, Y., Huang, Z., Yang, M., Jiang, X., Yang, J., Ke, S., Zhou, J., & Liu, G. (2025) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2025.3569784 · Cited by 2 · see citing works
1D and 2D Semiconducting Hybrid Nanostructures for Advanced Photodiodes
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A full 6 degree-of-freedom visual estimation with laser assisted
Liang, Z., Kang, Y., Wu, H., Wang, H., & Chen, G. (2023) · Measurement · doi:10.1016/j.measurement.2023.113099 · Cited by 1 · see citing works
Cu–Au alloy Schottky junction photodetectors on silicon for sub-bandgap near-infrared detection
Dudi, D., Bhardwaj, K., Panwar, S., & Mitra, A. (2026) · Journal of Applied Physics · doi:10.1063/5.0310718 · Cited by 1 · see citing works
Tang, X., Li, Y., Chen, D., Zhang, J., Zhang, Y., Liu, Y., Yao, X., Cheng, H., Jiang, Z., Peng, S., et al. (2026) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6c03502 · Cited by 1 · see citing works
Design of a High Speed dToF Ranging System
Meng, X., Li, Z., Li, J., Chen, K., Zhao, C., Zhao, J., & Deng, S. (2023) · IEEE International Conference on Information, Communication and Networks (ICICN) · doi:10.1109/icicn59530.2023.10392755 · Cited by 1 · see citing works
Zhang, Y., Shi, Y., Shen, J., Xu, R., Zhao, C., Chen, Y., & Zhan, C. (2025) · Applied Optics · doi:10.1364/ao.558949 · Cited by 1 · see citing works
Patel, S., Alnumay, Y., Brahim, A. A., Felemban, A., Alrasheed, A. J., Jifri, H., Parrott, B., & Abdellatif, F. (2022) · Measurement · doi:10.1016/j.measurement.2022.111482
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Nasiri, V., Sarli, R., & Afshari, S. (2023) · Advances in environmental engineering and green technologies book series · doi:10.4018/978-1-6684-8771-6.ch002
Jain, V. G. A. (2024) · Journal of Electrical Systems · doi:10.52783/jes.2061
Smart Optoelectronics in Health Monitoring and Human‐Machine Interactions
Gu, L., Lin, Y., & Zhang, Q. (2025) · doi:10.1002/9783527845507.ch8
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Sanganaikar, R. S., Mulangi, R. H., & Yatish, R. G. (2026) · Innovative Infrastructure Solutions · doi:10.1007/s41062-026-02816-6
- Authors
- You, J.-H., Oh, S., Park, J.-E., Song, H., & Kim, Y.-K.
- Corresponding author
- Kim, Young-Keun
- Venue
- Measurement
- Publisher
- Elsevier BV
- Published
- 2021-10
- Volume
- 183
- Pages
- 109817
- ISSN
- 0263-2241 (ISSN-L)
- OpenAlex
- W3176801351
- Cited by
- 31
- References
- 53
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 3 · 2023: 8 · 2022: 9 · 2021: 1
- FWCI
- 2.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Measurement (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Physics and Astronomy › Instrumentation › Advanced Optical Sensing Technologies
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- extrinsic calibration, photodetector arrays, autonomous vehicles, automotive assembly, ADAS, low-resolution LiDAR
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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