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.
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