JOURNAL ARTICLE

A 3D seam extraction and tracking method based on binocular structured light sensor

Abstract

To make the robot automatic welding systems more automatic and accurate, the 3D weld seam extraction has become a research hot-spot. In this paper, a seam extraction method for five types of straight-line seam based on point cloud obtained by three-dimensional reconstruction of binocular structured light is proposed. Firstly, the second derivative is used to calculate the inflection point for the rough extraction of seam characteristics. Secondly, according to the shape information of the welding workpiece, the center point of the seam is detected and the least square algorithm is used to fit the seam model. Finally, the 3D welding spot position and pose estimation are solved based on the established mathematical model. The experiments are conducted under five different situations, and the average extraction accuracy of the method can reach 0.19mm. The experimental results indicate that the proposed algorithm can efficiently locate five types of seam and generate the tracking path planning to guide robot manipulation.

Keywords:
Computer vision Computer science Point cloud Artificial intelligence Inflection point Robot welding Robot Position (finance) Tracking (education) Point (geometry) Welding Structured light Engineering Mathematics

Metrics

7
Cited By
0.37
FWCI (Field Weighted Citation Impact)
0
Refs
0.54
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Surface Roughness and Optical Measurements
Physical Sciences →  Engineering →  Computational Mechanics
Welding Techniques and Residual Stresses
Physical Sciences →  Engineering →  Mechanical Engineering
Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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