用于焊接环境三维建模的稀疏点云拟合  

Sparse point clouds fitting in 3D reconstruction for welding environment

作　　者：于兴华[1] 梁志敏[1] 高洪明[1] 张广军[1] 

机构地区：[1]哈尔滨工业大学现代焊接生产技术国家重点实验室,哈尔滨150001

出　　处：《焊接学报》2007年第6期109-112,共4页Transactions of The China Welding Institution

摘　　要：非结构化环境的三维重建是遥控焊接中虚拟现实的关键技术。采用立体视觉的方法进行焊接环境建模。由于焊接环境缺乏可用于立体匹配的特征点,所以采用向焊接工件添加标签的方法为立体匹配提供特征点。采用亚像素焦点检测算法及人机交互的立体匹配方法,得到焊接环境空间稀疏点云数据。在对点云进行拟合时,平面采用最小二乘法拟合,二次曲面采用Tikhonov正则化拟合。对于Tikhonov正则化参数的选取采用了准最优化方法。试验对平面工件和圆柱工件进行了三维重建,得到了工件的三维模型。结果表明,平面与曲面的拟合平均误差均小于1 mm,最大误差小于3 mm。3D reconstruction for non-structured environment is the key technology in virtual environment in remote welding.The welding environment was reconstructed based on stereo vision.Because welding environment is lack of feature points for stereo matching.The tags were added onto welding workpieces to provide feature points.Sub-pixel corner extraction and human-assist stereo matching was applied to acquire sparse point clouds of welding environment.The least square algorithm for plane fitting and Tikhonov regulation for quadric surface were used to fit the sparse point.Quasi-optimality criterion was used to choose the regulation parameter.The workpieces of plane and cylinder were reconstructed and the 3D models of workpieces were obtained.The results show that the fitting deviations for both planar and quadric models are all less than 1 mm,and the maximum deviations are less than 3 mm.

关 键 词：二次曲面拟合 三维重建 立体视觉 遥控焊接 

分 类 号：TP242.62[自动化与计算机技术—检测技术与自动化装置]