|Place of Conferral||中国科学院大学|
|Keyword||焊接机器人 视觉测量 结构光视觉 焊缝识别 点云分割 轨迹检测 路径规划 位姿模型|
1. 针对焊接机器人的三维测量需求，设计了基于数字光处理(Digital Light Processing，DLP)投影仪光栅投影系统，其作为焊接机器人的主动视觉测量系统；通过DLP投影仪的图案编程产生不同类型的编码图案，结合立体视觉系统，构造能够适应不同工况的视觉测量系统，满足焊接机器人在不同环境下三维测量的需求；对于视觉系统的各个关键单元进行了布局优化配置及部件选型，使之适应工业机器人末端有限的安装空间。
Welding technology is an extremely important processing means of industry manufacturing, and the welding robots are widely used in the modern manufacturing industry. At present, the "teaching-playback" mode and the off-line programming mode are two main operation modes of industrial robots. The "teaching-playback" mode is able to adapt to complex technological process and different welding objects. It is the most commonly used programming method for welding robots. However, for the 3D weld seam with complex trajectories, the teaching process exists some shortcomings, such as time-consuming, laborious, poor teaching precision and poor repeatability, so it is difficult to meet rapid, precision and flexible new manufacturing mode. The off-line programming mode can realize 3D path teaching of industrial robots with CAD technology. It can improve teaching efficiency in the structured industrial production environment. However, in the un-structured working environment, the off-line programming mode is difficult to achieve accurate and real-time reconstruction of virtual working environment, and cannot meet the dynamic, complex, multifarious welding requirements. Therefore, studying the automatic teaching mode and improving the efficiency and precision of 3D path teaching are the main research directions of the intelligent welding robots. The automatic identification and detection of weld seam are the pre-requisites for realizing the autonomous 3D path teaching of welding robots. In this paper, the key technologies of the autonomous path teaching of welding robots are studied, including seam type recognition, seam extraction, 3D seam path planning and precise positioning of weld seam. The paper’s main work is as follows:
Firstly, aiming at the 3D measurement requirements of welding robot, the grating projection system based on DLP projector is designed, which is used as the active vision measurement system of welding robots. Through the pattern programming of DLP projector, different types of coding patterns could generated. Combined with stereo vision system, an active vision measuring system is constructed to adapt to different working conditions and meet the 3D measurement requirements of welding robots in different environments. And layout optimization and component selection for each key unit of the designed vision system are done to adapt to the limited installation space of the end of the industrial robots.
Secondly, aiming at the detection and recognition problem of different types of narrow butt joints under poor contrast, an operator of feature extraction is designed to replace the traditional edge detection operators and realize seam extraction under poor contrast. By scanning the whole seam image, the location of seam center is extracted. On this basis, the feature vectors based on weld shape are designed to realize the feature extraction of different seam images. And a seam type detection method based on ANFIS model is proposed to realize the on-line detection and recognition of different weld seams.
Thirdly, aiming at the problem of robust and accurate feature extraction of different thick welds, based on 3D features of different weld seams, a 3D seam extraction algorithm based on point cloud segmentation is proposed. Through 3D reconstruction of welding workpieces, point cloud filtering, point cloud segmentation and feature extraction, the proposed algorithm could overcome the influence of weak texture, poor contrast, reflections from metallic surfaces, and imperfections on the work piece such as rust, mill scale and scratches which are not consistent from part to part and realize automatic 3D seam extraction of different types of thick plates.
Fourthly, aiming at the description problem of the position model and orientation model of the complex weld seam in 3D space, a path fitting method based on the cubic smoothing spline is proposed. The noise of the data to be fitted could be eliminated by introducing the roughness penalty function to ensure the smoothness and continuity of the weld seam path. A discrete dynamic coordinate system is established at each weld path point by processing the 3D point cloud data of the welding workpiece to construct a complete orientation model to describe different weld seams.
Fifthly, aiming at the problem of high-precision 3D measurement requirement of weld seams in welding robot system, based on the idea of coarse to fine planning, a weld seam extraction framework based on "coarse-fine " idea is proposed. Gray code patterns and laser stripe patterns are generated respectively by pattern programming of DLP projector, and the global vision and local vision of welding robot are constructed respectively. Through the coarse extraction and fine positioning of weld seam, the precision seam extraction of various types of weld seam can be achieved. Meanwhile, in order to achieve fast and precision extraction of various types of weld seam, a feature extraction algorithm based on kernel linear filtering algorithm is proposed. Based on the results of coarse seam extraction, by close-range scanning of the weld seam path, the seam path could be precisely positioned, and the mathematical model of the weld seam is corrected to improve the precision of seam extraction.
Finally, the research work of this paper is summarized, and the future research plans are proposed.
|杨磊. 基于DLP投影的焊接机器人焊缝识别和轨迹检测的技术研究[D]. 中国科学院大学. 中国科学院大学,2019.|
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