论文标题
通过点云模型的自动接缝提取的路径规划，用于机器人弧焊接
Path Planning with Automatic Seam Extraction over Point Cloud Models for Robotic Arc Welding
论文作者
论文摘要
本文介绍了基于点云的机器人系统用于电弧焊接。使用手势控件，系统扫描工件的部分点云视图，并通过线性迭代的最接近点算法将它们重建为完整的3D模型。然后，扩展了双边滤波器，以将工件模型变形并保留重要的几何信息。为了从模型中提取焊接接缝，提出了一种基于强度的算法，该算法检测边缘点并生成光滑的6-DOF焊接路径。这些方法在具有不同类型和姿势的多个工件上进行了测试。实验结果证明了该机器人系统对焊接应用的自动路径计划的鲁棒性和效率。
This paper presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical information. To extract the welding seam from the model, a novel intensity-based algorithm is proposed that detects edge points and generates a smooth 6-DOF welding path. The methods are tested on multiple workpieces with different joint types and poses. Experimental results prove the robustness and efficiency of this robotic system on automatic path planning for welding applications.
