周 扬,王 龙,来永斌.基于最优投影圆锥底面的罐口位姿测量方法[J].电子测量与仪器学报,2023,37(1):50-58
基于最优投影圆锥底面的罐口位姿测量方法
Measurement method of the tanker mouth pose basedon optimal projection cone bottom surface
  
DOI:10.13382/j.issn.1000-7105.2023.01.006
中文关键词:  双目视觉  3D 圆  投影椭圆锥  二义性  位姿测量
英文关键词:binocular vision  3D circle  projected elliptic cone  ambiguity  pose measurement
基金项目:国家自然科学基金(51705002, 11902002)项目资助
作者单位
周 扬 1.安徽理工大学机械工程学院 
王 龙 1.安徽理工大学机械工程学院 
来永斌 1.安徽理工大学机械工程学院 
AuthorInstitution
Zhou Yang 1.School of Mechanical Engineering, Anhui University of Science and Technology 
Wang Long 1.School of Mechanical Engineering, Anhui University of Science and Technology 
Lai Yongbin 1.School of Mechanical Engineering, Anhui University of Science and Technology 
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中文摘要:
      为了引导并联机器人装料过程中的自动对位,提出一种高精度的罐口位姿双目测量方法。 通过图像预处理提取罐口图 像上下边缘亚像素点,建立空间圆双目投影椭圆锥模型,在世界坐标系下构建椭圆锥底面,通过成像椭圆轮廓像素信息与椭圆 锥底面之间的映射关系,寻找最优圆锥底面所在坐标系得到目标姿态,利用姿态修正计算对应真实圆心像素所在位置,用双目 三角测量法得到世界坐标系下的圆心三维坐标。 针对空间圆投影二义性问题,提出利用罐口沿口消除二义性。 经仿真和实验 验证,算法精度高且能满足大角度姿态测量,实验测量姿态的最大误差为 1. 8°,真实圆心像素提取最大误差为 0. 98 pixels。 方 法无需任何辅助测量和约束条件,有效提高了装料过程中的自动化效率。
英文摘要:
      In order to guide the automatic decimal alignment of the parallel robot in the loading process, a high precision binocular measurement method of tanker mouth pose is proposed. The sub-pixels of the upper and lower edges of the tanker mouth image are extracted by image preprocessing. The binocular projection elliptical cone model of the spatial circle is established, and the bottom surface of the elliptical cone is constructed in the world coordinate system. Through the mapping relationship between the image pixels and the elliptic cone bottom, the optimal coordinate system of the cone bottom is found to obtain the target pose. The position of the pixel corresponding to the real center is calculated by pose correction, and the three-dimensional coordinates of the center in the world coordinate system are obtained by binocular triangulation. Aiming at the ambiguity problem of spatial circle projection, an ambiguity elimination method based on the tanker mouth height is proposed. The results of the simulation and experiment show that the algorithm has high accuracy and can meet the requirements of large angle pose measurement. The maximum error of the measured pose is 1. 8°, and the maximum error of the real center pixel extraction is 0. 98 pixels. The method does not need any auxiliary measurement and constraint conditions, and effectively improves the automatic efficiency in the loading process.
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