首页> 外文会议>Proceedings of the 2007 International Conference on Machine Learning and Cybernetics >VISION SYSTEM CALIBRATION OF AGRICULTURAL WHEELED-MOBILE ROBOT BASED ON BP NEURAL NETWORK
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VISION SYSTEM CALIBRATION OF AGRICULTURAL WHEELED-MOBILE ROBOT BASED ON BP NEURAL NETWORK

机译:基于BP神经网络的农用轮式机器人视觉系统标定。

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Camera calibration is the base of the machine vision based the autonomous navigation of the agricultural wheeled-mobile robots.There are the complex nonlinear relationship between the actual position points and the matched image points.Therefore the camera parameters have to be calculated by a precise imaging model.The more precise the imaging model requires, the more complicated the calibration becomes.it was proved that some traditional calibration methods, such as the method of Zhengyou Zhang, were inconvenient and their accuracy were also low.In this paper, according to the characteristic of the BP neural network, which can express any nonlinear relationship between inputs and outputs, a new method based on the BP neural network was applied to calibrate the vision system of an agricultural wheeled-mobile robot.The experimental results showed that this method was feasible and accurate.
机译:相机标定是基于农业轮式机器人自主导航的机器视觉的基础,实际位置点和匹配的图像点之间存在复杂的非线性关系,因此必须通过精确成像来计算相机参数成像模型要求的精度越高,校准就越复杂。事实证明,某些传统的校准方法(例如张正友的方法)不方便且精度也很低。 BP神经网络的特点是可以表达输入和输出之间的任何非线性关系,因此,基于BP神经网络的新方法被用于校准农用轮式机器人的视觉系统。可行和准确。

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