An efficient system based on model segmentation for weld seam grinding robot

Uneven surface quality often occurs when manual grinding butt welds, so robot welding seam grinding automation has become a fast-developing trend. Weld seam extraction and trajectory planning are important for automatic control of grinding process. However, the research on weld extraction is mostly focused on pre-welding. Due to the irregular shape of the weld after welding and the complex grinding process, there is seldom work that has been devoted to the weld grinding after welding. Consequently, a novel simple but efficient weld extraction algorithm is proposed in this paper, and the robot grinding path is planned. Firstly, a multi-degree of freedom bracket is designed for welding seam extraction. Secondly, the weld profile model is established, and a simple but effective weld extraction algorithm based on model segmentation is proposed to transform the calculating process of spatial point cloud into a two-dimensional point cloud calculating process. The least-square method (LSM) based on threshold comparison is used to segment the weld seam, which greatly improves the processing speed and accuracy. Then, the grinding path and grinding pose are calculated according to the extracted spatial structure of weld seam. Finally, an efficient robotic welding seam automatic grinding system based on model segmentation is built. Experiments’ results showed that the proposed method could make the irregular weld seam contour well-extract after welding and the built grinding system is efficient and reliable. The grinding efficiency is increased by 50%.