Paper
12 June 2020 A 3D seam extraction and tracking method based on binocular structured light sensor
Author Affiliations +
Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 115191Y (2020) https://doi.org/10.1117/12.2573270
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan
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.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lu Chen, Xiaohan Li, and Xiang Zhou "A 3D seam extraction and tracking method based on binocular structured light sensor", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 115191Y (12 June 2020); https://doi.org/10.1117/12.2573270
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Structured light

Clouds

Cameras

Imaging systems

Sensors

Calibration

3D modeling

Back to Top