表面视觉传感器模型参数的简易标定方法

FACILITATED METHOD TOCALIBRATE MODEL PARAMETERS OFVISION SENSOR FOR SURFACEMEASUREMENT

建立了基于多线结构光的表面视觉传感器的数学模型,提出了一种基于自由移动平面标定参照物的表面视觉传感器模型参数的简易标定方法。在自由移动的平面参照物上建立局部世界坐标系,将通过交比不变方法获得的各个光平面上特征点的局部世界坐标,变换到摄像机坐标系,从而获得已知三维的标定特征点。利用构建的位于不同光平面上标定特征点,可以实现工作状态的表面视觉传感器模型参数的优化估计。该标定方法降低了标定设备的成本,简化了标定过程,为表面视觉传感器的工程化应用奠定了基础。试验结果表明,该方法切实可行。

Based on the principle of multiple line structured light, the mathematical model of the surface vision sensor is established. A facilitated calibration approach to easily determine all the model parameters of a surface vision sensor with a planar reference object is proposed. The multiple local world coordinate systems are set up onto the different moving planes respectively. All the local 3D world coordinates of the control points falling on the multiple light stripe plane can be readily obtained by the invariance of the cross ratio. The 3D camera coordinates of the control points can be computed by transformation from the local world frames to the 3D camera coordinate frame. The optimization estimation of the model parameters of the surface vision sensor in the working state can be finished with those control points. The proposed approach greatly reduces the cost of the calibration equipment and simplifies the calibrating procedure, so it can promote the engineering applications of the surface vision sensor handily. It shows that this method is practical in the surface measurement by experiments.