Visual Locating of Reactor in an Industrial Environment Using the Composite Method To achieve an automatic unloading of a reactor during the sherardizing process, it is necessary to calculate the pose and position of the reactors in an industrial environment with various amounts of luminance and floating dust. In this study, the defects of classic image processing methods and deep learning methods used for locating the reactors are first analyzed. Next, an improved You Only Look Once(YOLO) model is employed to find the region of interest of the handling hole and a handling hole corner detection method based on the image morphology and a Hough transform is presented. Finally, the position and pose of the reactors will be obtained by establishing a 3D handling hole model according to the principle of a binocular stereo system. To test the performance of the proposed method, a set of experimental systems was set up and experiments were conducted. The results indicate that the proposed location method is effective and the precision of the position recognition can be controlled to within 4.64 mm and     1.68 xc2xb0     when the cameras are approximately 5 m away from the reactor, meeting the requirements.

LSD Based Vision Detection System for Industrial Robot under Complex Illumination Conditions In this paper, we present an object vision detection and localization method approach to the industrial robotic system under complex illumination conditions. In industrial applications of machine vision, many of feature extraction algorithms depend on edge detection, which can be affected by ambient illumination variation and loses efficacy. We propose a robust method that combines image enhancement, edge detection and feature information extraction to detect and locate target components. The key idea is to use a histogram key point constrained homomorphic filtering to enhance the image followed by line and arc segments feature detection. Finally, the experimental results on probe endface image dataset and steelmaking automation manufacture demonstrate the ability of the proposed method to perform more robust and accurate effectiveness under illumination variant conditions.