用定制标定板和优化算法，实现多激光雷达与摄像头的精准外参标定。
A Target-based Multi-LiDAR Multi-Camera Extrinsic Calibration System
- 基于定制ChArUco板和非线性优化，实现跨传感器标定。
- 实测数据验证方法有效性，标定精度满足自动驾驶需求。
- 适合多传感器融合系统开发人员使用。
外参标定是自动驾驶的核心环节，其精度直接影响感知系统的可靠性与车辆安全。现代车载传感器系统包含多种异构数据源，导致数据对齐难度加大。为此，本文提出一种面向多激光雷达与多摄像头系统的靶标式外参标定方案。该方法利用定制的ChArUco标定板，在有限先验知识下实现激光雷达与摄像头之间的交叉标定，并结合专门设计的非线性优化算法提升精度。在仓库环境中采集的真实数据上进行测试，结果表明所提方法有效，验证了该专用标定流程在多种传感器配置下的可行性。
原文摘要 · Abstract (English)
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.
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