<i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers
Modern visual perception techniques often rely on multiple heterogeneous sensors to achieve accurate and robust estimates. Knowledge of their relative positions is a mandatory prerequisite to accomplish sensor fusion. Typically, this result is obtained through a calibration procedure that correlates...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/3/956 |
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| author | Emanuele Giacomini Leonardo Brizi Luca Di Giammarino Omar Salem Patrizio Perugini Giorgio Grisetti |
| author_facet | Emanuele Giacomini Leonardo Brizi Luca Di Giammarino Omar Salem Patrizio Perugini Giorgio Grisetti |
| author_sort | Emanuele Giacomini |
| collection | DOAJ |
| description | Modern visual perception techniques often rely on multiple heterogeneous sensors to achieve accurate and robust estimates. Knowledge of their relative positions is a mandatory prerequisite to accomplish sensor fusion. Typically, this result is obtained through a calibration procedure that correlates the sensors’ measurements. In this context, we focus on LiDAR and RGB sensors that exhibit complementary capabilities. Given the sparsity of LiDAR measurements, current state-of-the-art calibration techniques often rely on complex or large calibration targets to resolve the relative pose estimation. As such, the geometric properties of the targets may hinder the calibration procedure in those cases where an ad hoc environment cannot be guaranteed. This paper addresses the problem of LiDAR-RGB calibration using common calibration patterns (i.e., A3 chessboard) with minimal human intervention. Our approach exploits the flatness of the target to find associations between the sensors’ measurements, leading to robust features and retrieval of the solution through nonlinear optimization. The results of quantitative and comparative experiments with other state-of-the-art approaches show that our simple schema performs on par or better than existing methods that rely on complex calibration targets. |
| first_indexed | 2024-03-08T03:48:55Z |
| format | Article |
| id | doaj.art-8b399c10b42546fc8176e26398df23ce |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T03:48:55Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8b399c10b42546fc8176e26398df23ce2024-02-09T15:22:23ZengMDPI AGSensors1424-82202024-02-0124395610.3390/s24030956<i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common MarkersEmanuele Giacomini0Leonardo Brizi1Luca Di Giammarino2Omar Salem3Patrizio Perugini4Giorgio Grisetti5Department of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyDepartment of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyDepartment of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyDepartment of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyDepartment of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyDepartment of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, 00185 Rome, ItalyModern visual perception techniques often rely on multiple heterogeneous sensors to achieve accurate and robust estimates. Knowledge of their relative positions is a mandatory prerequisite to accomplish sensor fusion. Typically, this result is obtained through a calibration procedure that correlates the sensors’ measurements. In this context, we focus on LiDAR and RGB sensors that exhibit complementary capabilities. Given the sparsity of LiDAR measurements, current state-of-the-art calibration techniques often rely on complex or large calibration targets to resolve the relative pose estimation. As such, the geometric properties of the targets may hinder the calibration procedure in those cases where an ad hoc environment cannot be guaranteed. This paper addresses the problem of LiDAR-RGB calibration using common calibration patterns (i.e., A3 chessboard) with minimal human intervention. Our approach exploits the flatness of the target to find associations between the sensors’ measurements, leading to robust features and retrieval of the solution through nonlinear optimization. The results of quantitative and comparative experiments with other state-of-the-art approaches show that our simple schema performs on par or better than existing methods that rely on complex calibration targets.https://www.mdpi.com/1424-8220/24/3/956LiDARcameraextrinsic calibration |
| spellingShingle | Emanuele Giacomini Leonardo Brizi Luca Di Giammarino Omar Salem Patrizio Perugini Giorgio Grisetti <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers Sensors LiDAR camera extrinsic calibration |
| title | <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers |
| title_full | <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers |
| title_fullStr | <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers |
| title_full_unstemmed | <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers |
| title_short | <i>Ca<sup>2</sup>Lib</i>: Simple and Accurate LiDAR-RGB Calibration Using Small Common Markers |
| title_sort | i ca sup 2 sup lib i simple and accurate lidar rgb calibration using small common markers |
| topic | LiDAR camera extrinsic calibration |
| url | https://www.mdpi.com/1424-8220/24/3/956 |
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