Intelligent product assembling method based on machine vision recognition

Abstract

According to the invention, a method of combining deep learning and traditional digital image processing is adopted; according to the method, the detection precision and the detection speed are comprehensively considered, rough position information of an object can be detected in a complex environment by adopting a deep learning target detection algorithm, then the detected position is used as a region of interest, and image processing is performed to detect more accurate target contour information. According to the invention, a target detection method based on deep learning is improved, so that the detection speed and the detection precision are improved, requirements on workshop hardware are greatly reduced, and the production cost is reduced. In conclusion, the assembly efficiency and the assembly precision of parts are greatly improved, and the situation that assembly fails due to deviation of the positions of the parts is reduced.

Description

technical field [0001] The invention belongs to the technical field of automobile production, and in particular relates to a product intelligent assembly method based on machine vision recognition. Background technique [0002] There are many parts in the car production process that need to be assembled. Traditional manual assembly requires a lot of manpower and low material production efficiency, which can no longer meet the current automated production. At present, most of the common automated parts assembly production lines teach the robot, and then assemble the parts at a fixed position. However, position deviation will inevitably occur when the parts are transferred to a fixed position. At this time, assembling parts according to the fixed robot teaching position will lead to assembly failure and even damage to the parts. In order to solve this problem, the present invention adopts the method of computer vision to locate the assembly position of the parts to be assemb...

AI Technical Summary

Problems solved by technology

[0004] On the other hand, the parts assembly production line needs automated automatic assembly equipment. However, the position of the ordinary robot teaching method is fixed. When there is a slight deviation in the position of the parts, the automatic equipment will fail to assemble and damage the assembled parts.