A Target-based Multi-LiDAR Multi-Camera Extrinsic Calibration System
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911283773702144 |
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| author | Gentilini, Lorenzo Serio, Pierpaolo Donzella, Valentina Pollini, Lorenzo |
| author_facet | Gentilini, Lorenzo Serio, Pierpaolo Donzella, Valentina Pollini, Lorenzo |
| contents | Extrinsic Calibration represents the cornerstone of autonomous driving. Its accuracy plays a crucial role in the perception pipeline, as any errors can have implications for the safety of the vehicle. Modern sensor systems collect different types of data from the environment, making it harder to align the data. To this end, we propose a target-based extrinsic calibration system tailored for a multi-LiDAR and multi-camera sensor suite. This system enables cross-calibration between LiDARs and cameras with limited prior knowledge using a custom ChArUco board and a tailored nonlinear optimization method. We test the system with real-world data gathered in a warehouse. Results demonstrated the effectiveness of the proposed method, highlighting the feasibility of a unique pipeline tailored for various types of sensors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_16621 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Target-based Multi-LiDAR Multi-Camera Extrinsic Calibration System Gentilini, Lorenzo Serio, Pierpaolo Donzella, Valentina Pollini, Lorenzo Robotics Computer Vision and Pattern Recognition Extrinsic Calibration represents the cornerstone of autonomous driving. Its accuracy plays a crucial role in the perception pipeline, as any errors can have implications for the safety of the vehicle. Modern sensor systems collect different types of data from the environment, making it harder to align the data. To this end, we propose a target-based extrinsic calibration system tailored for a multi-LiDAR and multi-camera sensor suite. This system enables cross-calibration between LiDARs and cameras with limited prior knowledge using a custom ChArUco board and a tailored nonlinear optimization method. We test the system with real-world data gathered in a warehouse. Results demonstrated the effectiveness of the proposed method, highlighting the feasibility of a unique pipeline tailored for various types of sensors. |
| title | A Target-based Multi-LiDAR Multi-Camera Extrinsic Calibration System |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.16621 |