The integration of camera and LiDAR technologies has the potential to significantly enhance construction robots’ perception capabilities by providing complementary construction information. Structured light cameras (SLCs) are a desirable alternative as they provide comprehensive information on construction defects. However, fusing these two types of information depends largely on the sensors’ relative positions, which can only be established through extrinsic calibration. This paper introduces a novel calibration algorithm considering a customized board for SLCs and repetitive LiDARs, which are designed to facilitate the automation of construction robots. The calibration board is equipped with four symmetrically distributed hemispheres, whose centers are obtained by fitting the spheres and adoption with the geometric constraints. Subsequently, the spherical centers serve as reference features to estimate the relationship between the sensors. These distinctive features enable our proposed method to only require one calibration board pose and minimize human intervention. We conducted both simulation and real-world experiments to assess the performance of our algorithm. And the results demonstrate that our method exhibits enhanced accuracy and robustness.

中文翻译：

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结构光相机和重复激光雷达的自动外在校准

相机和激光雷达技术的集成有可能通过提供互补的施工信息来显着增强建筑机器人的感知能力。结构光相机 (SLC) 是理想的替代方案，因为它们可以提供有关施工缺陷的全面信息。然而，融合这两类信息在很大程度上取决于传感器的相对位置，而这只能通过外部校准来建立。本文介绍了一种新颖的校准算法，考虑了 SLC 和重复 LiDAR 的定制板，旨在促进建筑机器人的自动化。标定板装有四个对称分布的半球，通过球体拟合并采用几何约束得到其中心。随后，球心作为参考特征来估计传感器之间的关系。这些独特的功能使我们提出的方法只需要一个校准板姿势并最大限度地减少人为干预。我们进行了模拟和现实实验来评估我们算法的性能。结果表明，我们的方法表现出更高的准确性和鲁棒性。