中国科学院自动化研究所机构知识库

In the modern manufacturing, the teaching-playback mode and the off-line programming mode of the welding robots still play the important roles. However, these modes cannot meet the autonomous and adaptive capabilities of the welding robots. To improve the flexibility of the welding robots, fast and accurate seam extraction is the key link to realize the intelligent welding robots. A fast and accurate seam extraction algorithm based on the novel structured light vision system is proposed in this paper. First, the digital light processing projector is used to construct the multi-function structured light vision sensor in this paper. It could generate different pattern images to adapt different welding tasks. Second, during the current research work about seam extraction, the seam extraction algorithm based on morphological image processing has been widely used and improved. However, these algorithms include much machine vision algorithms and the speed of these algorithms is too slow to meet real-time requirements. Meanwhile, these algorithms are difficult to adapt to different types of weld seam. In order to achieve fast and accurate extraction of various types of weld seams, the target tracking algorithm based on the kernelized correlation filters algorithm is applied into this paper. Experimental results show that the proposed method could well realize fast and accurate seam extraction of various types of weld seams.