A Sinusoidal Swing Welding Method for Straight Line and Arc Trajectory of Arc Welding Robot
Due to the particularity of arc welding robot operation, the accuracy of robot trajectory planning is required to be high. Which requires not only specifying a series of parameters to describe the desired trajectory, but also adding the welding torch swing to obtain better welding performance. For straight line and arc trajectory, a swing welding method based on the combination of straight line sine swing welding and are sine swing welding is proposed to improving the process application accuracy of swing welding. Firstly, the coordinate information of the main welding track points is obtained through teaching, and the radius and center angle of the arc are determined; The polar coordinate method is used to describe the trajectory points of sinusoidal swing welding. Its programming and conversion are relatively simple, reducing the complexity of the algorithm and the possible errors arising therefrom; Finally, through the joint simulation of MATLAB and RobotStudio softwares, the sine swing welding algorithm is transplanted to RobotStudio software, and the guide rail, workpiece coordinate system and tool coordinate system are transformed into (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$x, y, z$</tex>) offset and rotation matrix under XYZ coordinate system. The experimental results show that the algorithm is simple, convenient and easy to implement, which provides a reference for swing welding, and has certain theoretical value and practical significance.
Authors
- Minsi Li (ORCID: https://orcid.org/0009-0003-5771-4557)
- Ming Xin (ORCID: https://orcid.org/0000-0002-9947-6986)
- Haiyan Liu (ORCID: https://orcid.org/0000-0002-4244-027X)
- Ting Chen (ORCID: https://orcid.org/0000-0001-9165-8331)
Institutions
- Guangxi University of Science and Technology (CN)
- Nanning Normal University (CN)
Publication Details
- Published
- 2025-04-28
- DOI
- https://doi.org/10.1109/icaidt66272.2025.00085
- Primary Topic
- Robot Manipulation and Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00