Setting method for universal vision localization system

Abstract

The invention relate to a setting method for a universal vision localization system. The method includes steps of 1, camera setting; 2, algorithm setting; 3; setting implementation. In the first step, a camera selecting module selects a camera of a determined specification for taking a picture; the picture is subjected to focal length adjustment and picture taking exposure value adjustment through a picture modulation module; a coordinate calibration module sets a coordinate origin value of robot starting according to the taken picture; a communication protocol module adopts a serial port RS232 for setting a TCP / IP protocol of a computer; and the image signals and the coordinate signals are input into a vision positioning system through the communication protocol module. In the second step, a collection card module stores picture signals; an algorithm module calls a determined algorithm from an algorithm base for analysis and treatment on the pictures signals; a logic output module outputs data analysis and treatment formats and calculation conditions to a robot. In the third step, an operation state is entered; the vision system realizes information connection with the robot through setting an on-line state and the robot performs accurate grabbing on products.

Description

technical field [0001] The invention relates to a general vision system, in particular to a setting method of a general vision positioning system. Background technique [0002] The machine vision system is to use machines instead of human eyes for measurement and judgment. The vision system refers to converting the ingested target into an image signal through machine vision products, sending it to a dedicated image processing system, and converting it into a digital signal according to pixel distribution, brightness, color and other information; the image system performs various calculations on these signals. Extract the characteristics of the target, and then control the on-site equipment action according to the result of the discrimination. It can measure, guide, detect, and identify the product on the fastest production line, and can complete the production task with quality and quantity. Machine vision systems generally include light sources, lenses, CCD cameras, image ...

AI Technical Summary

Problems solved by technology

During the development process of the vision system, the programmer can choose the corresponding algorithm according to the customer's needs. For example, if the customer needs the robot to guide the alignment, the pattern matching tool in the algorithm library is called to guide the robot to accurately grasp the material, but the disadvantages Because: 1. The long development cycle is not conducive to the overall development progress of customer projects; the professional technical level of developers is high, and the number of personnel is large, especially in the current shortage of high-tech talents in the visual industry

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