解决旋转平台与激光雷达间的静态标定问题，提升3D扫描精度。
Two-Stage Extrinsic Calibration of a Static Line-Scanning Lidar with a Rotary Platform
- 分两阶段自动标定旋转轴与激光雷达的相对位置
- 在真实数据集上验证，收敛性良好且误差可控
- 适合需要高精度工业检测的激光扫描系统
线扫描激光雷达在固定平面内获取距离和方位信息。为实现周围物体的三维感知，需使雷达扫描平面与物体间存在相对运动。因此，在工业场景中使用旋转平台进行精确扫描或检测具有广阔前景，也是本文重点。在旋转平台设置下，若已知旋转轴及其精确运动，则可构建物体的三维点云。然而该方案带来关键问题：如何准确确定平台旋转轴相对于激光雷达坐标系的位置？这在机器人领域被称为标定问题。任何此变换的不准确性都会直接影响重建点云质量，导致目标物体失真。本文探索了自动化方法，对静态与动态条件下旋转平台轴心相对于静态线扫描激光雷达的变换关系进行估计。所提算法已在自研旋转平台及调频连续波（FMCW）激光雷达的真实数据集上验证，并研究了不同初始条件下的收敛特性。
原文摘要 · Abstract (English)
A line-scanning lidar yields range and azimuth values in a fixed plane. To perceive surrounding objects in 3D, there must be relative motion between the lidar plane and the object. Thus, using a rotating base-platform is promising for industrial applications where objects need to be scanned or inspected precisely, and is the main focus of this work. In the rotary platform setup, a 3D point cloud of an object can be constructed if the axis of rotation and the precise motion about that axis are known. However, this setup gives rise to the following problem: how can the axis of rotation of the platform be accurately identified with respect to the lidar coordinate system? It is referred to as the calibration problem in the robotics community. Any inaccuracy in this transformation directly affects the quality of the reconstructed point cloud, leading to misrepresentation of the object of interest. In this work, we explore automated approaches to statically and dynamically estimate the transformation of a rotary platform's axis of rotation with respect to a static line-scanning lidar. The proposed algorithms have been validated on real-world datasets obtained from a custom made rotary platform and an FMCW lidar, and their convergence characteristics are studied for various initial conditions.
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