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基于椭圆线轮廓度误差评定的椭圆提取方法 被引量:4
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作者 彭凯 刘书桂 +1 位作者 张雪飞 黄风山 《光电工程》 EI CAS CSCD 北大核心 2006年第12期101-104,共4页
简要介绍了目标测头视觉坐标测量系统,分析了测量系统成像目标的图像特征。在此基础上,提出了一种识别和提取CCD图像中目标椭圆的新方法。该方法对CCD图像中的每一个封闭轮廓进行椭圆拟合,根据评价椭圆形状误差的线轮廓度大小来判定该... 简要介绍了目标测头视觉坐标测量系统,分析了测量系统成像目标的图像特征。在此基础上,提出了一种识别和提取CCD图像中目标椭圆的新方法。该方法对CCD图像中的每一个封闭轮廓进行椭圆拟合,根据评价椭圆形状误差的线轮廓度大小来判定该轮廓是否为目标椭圆轮廓。实际检测结果表明,该算法原理正确,易于编程实现,能有效剔除噪音图像,准确提取目标椭圆,具有广泛的实用性。 展开更多
关键词 视觉坐标测量 椭圆线轮廓度误差 目标椭圆
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Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network 被引量:1
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作者 Su, J. Pan, Q. Xi, Y. 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2001年第3期45-50,共6页
A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation ... A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity. 展开更多
关键词 Adaptive algorithms Computational complexity Computer simulation coordinate measuring machines Error detection Mathematical models Neural networks Robotic arms Robustness (control systems) Stereo vision
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Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part 被引量:1
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作者 Pongsak Joompolpong Pradit Mittrapiyanuruk Pakorn Keawtrakulpong 《Journal of Electronic Science and Technology》 CAS CSCD 2016年第1期80-86,共7页
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... 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. 展开更多
关键词 3D pose estimation coordinate measurement coordinate measuring robot robot vision vision 3D coordinate measurement
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