Binocular vision-based workpiece grabbing method

Abstract

The present invention relates to a binocular vision-based workpiece grabbing method. The method includes following steps that: (1) a binocular vision system is calibrated; (2) a left camera and a right camera simultaneously collect images and correct the images; (3) a template matching algorithm is adopted to identify and position a workpiece in the left image and right image; (4) the three-dimensional attitude of the workpiece is calculated according to the identification and positioning information of the workpiece of the images of the left camera and the right camera; and (5) an industrial robot automatically grabs the workpiece according to the three-dimensional attitude information. The binocular vision-based workpiece grabbing method of the invention has the advantages of high real-time performance, high applicability, accurate grabbing, high working efficiency and the like.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a binocular vision-based workpiece grasping method. Background technique [0002] With the continuous development of manufacturing and manufacturing, people's requirements for automation continue to increase, and traditional manufacturing methods (manual operation or simple mechanical production) are constantly being challenged. An industrial robot is a multi-joint manipulator or a multi-degree-of-freedom machine device for the industrial field. It can perform work automatically. It is a machine that realizes various functions by its own power and control capabilities. It has been used more and more widely, but now industrial robots generally need to run according to pre-programmed programs, requiring complex debugging in the early stage, which does not satisfy more flexible and flexible production. [0003] In recent years, machine vision is commonly used to replace arti...

AI Technical Summary

Problems solved by technology

The existing method uses a monocular camera to collect the image of the workpiece, identifies and locates the workpiece, and then transmits the pose information of the workpiece to the industrial robot for subsequent processing by the robot. However, the monocular vision cannot obtain the three-dimensional information of the workpiece, so this only It is suitable for grasping workpieces with small thickness and good consistency, but the versatility is not strong

Using vision to collect images, the workpiece may appear differently in the field of view of the industrial camera. Therefore, the image recognition algorithm needs to solve the problem of zooming, rotating or inconsistent brightness of the workpiece in the image. The existing recognition algorithm method is still not very good. solve these problems

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