大型多传感器工业机器人单元的视觉标记引导点云配准

Erind Ujkani, J. Dybedal, Atle Aalerud, Knut B. Kaldestad, G. Hovland
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引用次数: 10

摘要

本文给出了大型工业机器人单元三维传感器标定的基准和精度分析。使用的传感器是Kinect v2,它包含一个RGB和一个基于飞行时间原理测量深度的红外相机。所采取的方法是基于一种结合Aruco视觉标记、使用感兴趣区域和迭代最近点的方法的新方法。传感器的校准是成对进行的,利用了飞行时间传感器在生成的点云数据中可能有一些重叠的事实。对于尺寸为10m × 14m × 5m的体积,使用6个传感器节点生成的点云数据的典型精度为5-10cm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual Marker Guided Point Cloud Registration in a Large Multi-Sensor Industrial Robot Cell
This paper presents a benchmark and accuracy analysis of 3D sensor calibration in a large industrial robot cell. The sensors used were the Kinect v2 which contains both an RGB and an IR camera measuring depth based on the time-of-flight principle. The approach taken was based on a novel procedure combining Aruco visual markers, methods using region of interest and iterative closest point. The calibration of sensors is performed pairwise, exploiting the fact that time-of-flight sensors can have some overlap in the generated point cloud data. For a volume measuring 10m × 14m × 5m a typical accuracy of the generated point cloud data of 5–10cm was achieved using six sensor nodes.
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