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Visual Marker Guided Point Cloud Registration in a Large Multi-Sensor Industrial Robot Cell

Erind Ujkani, Joacim Dybedal, Atle Aalerud, Knut Berg Kaldestad, Geir Hovland

发表年份
2018
引用次数
12

摘要

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.

关键词

Point cloudComputer visionComputer scienceArtificial intelligenceCalibrationBenchmark (surveying)RobotPoint (geometry)Iterative closest pointRGB color model

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