基于机器视觉的工业机器人分拣技术研究

Research on Sorting Technology of Industrial Robots Based on Machine Vision

随着现代工业自动化程度的提高,分拣技术作为物流系统中的重要环节,其效率与准确性对整个生产流程具有重要影响。构建一种视觉系统,摄像机被用来获取分拣区域内金属工件的图像序列。这些图像序列经过一系列预处理操作,包括灰度化、滤波去噪等,以提高图像的清晰度和识别率。预处理之后,采用霍夫圆检测算法对图像中的圆形物体进行检测,以识别出规则几何形状的工件。角点检测算法则被用于确定工件的位置和方向信息。通过提取图像中的角点,可以准确定位工件的位置,并根据角点的分布情况计算出工件的方向,为后续的分拣提供依据。实验表明该系统能解决工件的分拣问题,达到分拣目的,提高分拣速度和精度,适应各种复杂工件的分拣需求。这对于提高现代工业生产效率、降低成本具有重要的意义。

With the improvement of modern industrial automation,sorting technology,as an important link in logistics systems,its efficiency and accuracy have a significant impact on the entire production process.A visual system is constructed.The camera is used to obtain a sequence of images of metal workpieces in the sorting area.These image sequences go through a series of pre-processing operations,including grayscale,filtering,and sterilization,to improve the clarity and recognition rate of the images.After pre-processing,the Hough Circle Detection algorithm is used to detect circular objects in the image to identify workpieces with regular geometric shapes.The corner detection algorithm is used to determine the position and direction of the workpiece.By extracting vertices from the image,the position of the workpiece can be pinpointed,and the direction of the workpiece can be calculated based on the distribution of vertices,providing a basis for subsequent sorting.The experiment shows that the system can solve the sorting problem of workpieces,achieve sorting goals,improve sorting speed and accuracy,and adapt to the sorting needs of various complex workpieces.This is of great importance for improving modern industrial production efficiency and reducing costs.