线结构光视觉传感器与CMM集成的一种标定算法

A CALIBRATION ALGORITHM FOR INTEGRATION OF STRUCTURED LIGHT VISION SENSOR WITH CMM

  • 摘要: 建立了视觉传感器仿射坐标系,在给出仿射坐标系与CMM坐标系初始转换矩阵的条件下用函数逼近方法拟合出视觉传感器映射关系,并在此基础上采用基于目标特征点的优化算法来反复修正仿射坐标系与CMM坐标系之间的转换关系,使坐标转换矩阵估计参数收敛于最小二乘意义下的最优值,实现了视觉传感器建模及其与CMM的集成.本文最后给出了标定实验结果.

     

    Abstract: A novel calibration algorithm is presented to integrate structured-light vision sensor into coordinate measuring machine.The system modeling is decomposed into two interactive parts:establishing the model of structured-light vision sensor and calculating the transformation between skewed vision sensor and CMM Cartesian world frame. A B-spline function is applied to approximate the mapping model of structuredlight vision sensor in the skewed sensor frame. Given initial coordinate transformation matrix, sample points for establishing B-spline function in the skewed sensor frame is calculated and B-spline function can be obtained by an iterative adjustment approach. Then, a nonlinear constrainted optimization algorithm is used to adjust the coordinate transformation matrix and B-spline function model of vision sensor is refreshed. The above procedure is repeated until an stable optimal transformation matrix is obtained. an experiment is presented.

     

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