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  • 迪奧科技標語
    Analysis of Industrial Robots' Visual Positioning Technology
    Author:Administrator   Published in:2020-01-10 17:35

    The robot integrates electronic technology, sensing technology, and intelligent control technology. It is a machine device that can automatically perform work tasks. It can accept human commands and can act autonomously in accordance with the principles and programs formulated by artificial intelligence technology. The field has been applied.

    At present, industrial robots can only execute predetermined command actions in a strictly defined structured environment, and lack the ability to sense and respond to the environment, which greatly limits the application of robots. Workpiece visual positioning method, in conjunction with dedicated image processing software, utilizes the robot's visual control without the need to teach or traverse the industrial robot's motion trajectory in advance. It can achieve reliable positioning of the industrial robot's vision system, and improve workpiece positioning accuracy and It has played a positive role in processing effects, which can save a lot of programming time and improve production efficiency and processing quality. This aspect in China is mainly used for tracking of welding seams by welding robots.

    First, the composition of the visual positioning system

    The robot vision positioning system is structured (as shown in the figure below). Spraying tools and a single camera are installed at the end of the articulated robot, so that the workpiece can fully appear in the camera image. The system includes a camera system and a control system:

    (1) Camera system: It consists of a single camera, a computer, and an acquisition system (including an image acquisition card). It is responsible for the collection of visual images and machine vision algorithms. This system recommends the use of a digital camera. The extraction accuracy is higher than that of a general camera. .

    (2) Control system: It consists of a computer and a control box to control the actual position of the end of the robot; 

    The CCD camera is used to shoot the work area, and the computer uses the image recognition method to extract the tracking features and perform data recognition and calculation.


    Fig. 1 Composition of Vision Positioning System of Spraying Robot

    Working principle of visual positioning system

    Using the American TEO brand digital camera TM-C6597E, equipped with TM-C520HP image acquisition system, designed by a dedicated camera, balanced transmission line, image acquisition card, the three are unified, the video signal is input to the calculator and processed quickly. First, a local image of the tracked object is selected. This step is equivalent to the offline learning process. A coordinate system is established in the image and the training system is used to find the tracked object. After the study, the image card continuously collects images, extracts tracking features, performs data identification and calculation, solves the given position of the joints of the robot through inverse kinematics, and finally controls the high-precision end effector to adjust the position of the robot.

    In this way, the vision positioning system combines region-based matching and shape feature recognition, performs data recognition and calculation, and can quickly and accurately identify the boundaries and centers of object features. The robot control system obtains the rotation angles of the joints of the robot through inverse kinematics. Error, and finally control the high-precision end effector, adjust the pose of the robot to eliminate this error. This solves the problem that the actual position of the end of the robot is far from the expected position, and improves the positioning accuracy of the traditional robot.

    Third, image feature extraction

    The contrast between the workpiece on the workbench and the background of the workbench is very different in color, that is, the work is identified as black, the center line of the black image is extracted, and the acquisition system uses this information as an important feature to identify the work.

    When a general vision system obtains a workpiece image, it cannot be used directly in the vision system due to various conditions and noise interference. It must be image pre-processing such as gray correction and noise filtering after image analysis and recognition.

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