基于旋转平台的静态线扫描激光雷达的两阶段外部校准
Two-Stage Extrinsic Calibration of a Static Line-Scanning Lidar with a Rotary Platform
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中文总结 AI 辅助
研究基于旋转平台的静态线扫描激光雷达校准问题，探索自动方法静态和动态估计旋转轴变换，通过真实数据集验证算法并研究其收敛特性。
中文摘要 AI 辅助
线扫描激光雷达在固定平面内产生距离和方位值。为了三维感知周围物体，激光雷达平面和物体之间必须有相对运动。因此，使用旋转基座平台对需要精确扫描或检查物体的工业应用很有前景，这也是本文主要研究内容。在旋转平台设置中，如果旋转轴和绕该轴的精确运动已知，就可以构建物体的三维点云。然而，该设置存在一个问题：如何相对于激光雷达坐标系准确识别平台的旋转轴？这在机器人领域被称为校准问题。这种变换中的任何不准确都会直接影响重建点云的质量，导致对感兴趣物体的错误表示。在这项工作中，我们探索了自动方法来静态和动态估计旋转平台的旋转轴相对于静态线扫描激光雷达的变换。所提出的算法已在从定制旋转平台和调频连续波激光雷达获得的真实数据集上得到验证，并针对各种初始条件研究了它们的收敛特性。
英文摘要
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.
发表机构
- SiLC Technologies（SiLC技术公司）
机构由 AI 辅助整理，请以论文原文为准。
