改进的工程机器人立体视觉标定方法

针对摄像机线性标定准确程度不高与非线性标定计算复杂等问题,以己知的三维信息为基础推导二维像素点对信息,提出了基于神经网络的三目立体视觉摄像机标定方法,构建了改进的BP神经网络模型,对比分析了两种摄像机标定方法的像素点对均方根误差。结果表明:采用改进的BP神经网络能够避免对摄像机进行非线性建模,有利于提高标定精度,增加系统的灵活性,更具有实际意义。

Modified stereo vision calibration method for construction robot

To overcome the shortcoming of the linear and non-linear calibration in the processing of camera calibration,the 2-D pixels information was deduced based on the foregone 3-D information,a new intelligent calibration algorithm was presented based on neural network and an improved BP network model was constructed,and pixels point errors in two-sort calibration methods were compared.The experiment results indicate that the improved BP network model can avoid non-linear modeling and enhance the calibration precision and the flexibility,which has real significance.