期刊文献+

Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part 被引量:1

Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part
下载PDF
导出
摘要 In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine(CMM).Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error(RMSE) of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods. In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine(CMM).Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error(RMSE) of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.
出处 《Journal of Electronic Science and Technology》 CAS CSCD 2016年第1期80-86,共7页 电子科技学刊(英文版)
基金 wsupported by the Thailand Research Fund and Solimac Automation Co.,Ltd.under the Research and Researchers for Industry Program(RRI)under Grant No.MSD56I0098 Office of the Higher Education Commission under the National Research University Project of Thailand
关键词 3D pose estimation coordinate measurement coordinate measuring robot robot vision vision 3D coordinate measurement 3D pose estimation coordinate measurement coordinate measuring robot robot vision vision 3D coordinate measurement
  • 相关文献

参考文献12

  • 1S. Zhu and Y. Gao, "Noncontact 3-D coordinate measurement of cross-cutting feature points on the surface of a large-scale workpiece based on the machine vision method," 1EEE Trans. Instrumentation and Measurement, vol. 59, no. 7, pp. 1874-1887, 2010.
  • 2D. Zhang, J. Liang, and C. Guo, "Photogrammetric 3D measurement method applying to automobile panel," in Proc. of the 2nd lntl. Conf. Computer and Automation Engineering (ICCAE), 2010, pp. 70-74.
  • 3S.-G. Liu, K. Peng, F.-S. Huang, G.-X. Zhang, and P. Li, "A portable 3D vision coordinate measurement system using a light pen," Key Engineering Materials, vol. 295-296, pp. 331-336, Oct. 2005.
  • 4K. Peng, L.-B. Lin, and X.-L. Zhou, "Error analysis and compensation of 3D coordinate measuring system by watching an image of object," in Proc. of the 2nd Intl. Congress on linage and Signal Processing, 2009, pp. 1-5.
  • 5R. Sato, K. Kato, and K. Harada, "Development of the hole position inspection system of pressed car parts by usinglaser 3-d measurement," in Proc. of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, 2013, pp. 317-322.
  • 6S. Malassiotis and M. G. Strintzis, "Stereo vision system for precision dimensional inspection of 3D holes," Machine Vision Applications, vol. 15, no. 2, pp. 101-113, 2003.
  • 7K. S. Artm, T. S. Huang, and S. D. Blostein, "Least-squares fitting of two 3-D point sets," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. PAMI-9, no. 5, pp. 698-700, Sep. 1987.
  • 8U. Markus, W. Christian, and S. Carsten, "CAD-based recognition of 3D objects in monocular images," in Proe. of IEEE Intl. Conf. on Robotics and Automation, 2009, pp. 1191-1198.
  • 9S. Remy, M. Dhome, J. M. Lavest, and N. Daucher, "Hand-eye calibration," in Proc. of the 1997 IEEE/RSJ Intl. Conf. IROS '97. Intelligent Robots and Systems, 1997, pp. 1057-1065.
  • 10C. Steger, "Occlusion, clutter, and illumination invariant object recognition," Intl. Archives of Photogrammetry and Remote Sensing, vol. 34, part 3A, pp. 345-350, 2002.

同被引文献9

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部