Authors

Abstract

As a kind of intelligent agricultural equipment, picking robots are of great significance for improving the efficiency of agricultural production. However, the main bottleneck restricting the development of picking robots today is the positioning and control in image recognition. Therefore, an agricultural picking control method based on visual servo technology is proposed. This method can accurately control the picking hand of the picking robot on the basis of building an eye-hand relationship model and an online identification system. With the tomato picking process as the background, the effectiveness of the method was verified. The image feature point test results show that the error between the stable feature point of the picking robot and the expected image feature point is only. In addition, the image plane trajectory of the picking robot is relatively smooth, and there is no vibration or overshoot. In addition, from its density distribution characteristics, it can be seen that the picking hand movement is a continuous acceleration stage at the beginning of the control, and at the end of the control, the characteristic points gradually tend to the desired characteristics, and the output of the control system is relatively stable. It can be seen from this that the model has better control performance. This method has certain practical significance for the improvement of agricultural picking efficiency.

Abstract in Chinese

采摘机器人作为一种智能农业设备，对提高农业生产效率具有重要意义。然而，目前制约采摘机器人发展的主要瓶颈是图像识别中的定位与控制。为此，提出了一种基于视觉伺服技术的农业采摘控制方法。该方法在建立眼-手关系模型和在线辨识系统的基础上，能够准确地控制采摘机器人的拣手。以番茄采摘过程为背景，验证了该方法的有效性。图像特征点测试结果表明，采摘机器人的稳定特征点与期望的图像特征点之间仅存在误差。另外，拾取机器人的像面轨迹比较平滑，没有振动和过冲现象。另外，从其密度分布特征可以看出，采摘手的运动在控制开始时是一个连续的加速阶段，在控制结束时，特征点逐渐趋向于期望的特性，控制系统的输出相对稳定。由此可见，该模型具有较好的控制性能。该方法对提高农业采摘效率具有一定的现实意义。