全维视觉机器人距离标定方法

Methods of distance calibration for omni-directional robot

通过分析全维视觉系统的特点,总结出了常用全维视觉系统距离的标定方法,指出了各自的应用范围及优缺点。并针对应用范围最广的插值标定方法存在"单个采样点对标定精度影响较大"的缺点,提出了一种利用人工神经网络进行标定的新方法。实验证明,该距离标定方法不但可以节省标定时间,还可以提高标定精度。

Several widely used calibration methods as well as their applied range, advantage and disadvantage were summarized based on analyzing the characteristic of the omnidirectional vision system. Because of the disadvantage of the embolic method, which was the single sample could badly affect the calibrating precision, a new calibrating method was proposed, which used the neural network to make distance calibration. The experiment shows that the method can save the calibration time and improve the calibration precision.