Visual identification method and device for single-category unstacking, equipment and medium

Abstract

The invention discloses a visual identification method and device for single-category unstacking, equipment and a medium, and belongs to the field of machine vision, and the visual identification method comprises the steps: carrying out the filtering and down-sampling of an original 3D point cloud of a to-be-unstacked object, and obtaining a target point cloud; performing boundary extraction on the target point cloud to obtain boundary point cloud, wherein the boundary point cloud only comprises contour points; performing 3D matching on a preset template point cloud and the boundary point cloud, and segmenting out each workpiece contour point cloud matched with the preset template point cloud from the boundary point cloud, the preset template point cloud being a contour point cloud consistent with each workpiece type in the to-be-unstacked object; and obtaining workpiece poses corresponding to the workpiece contour point clouds obtained through matching, and performing unstacking according to height information in the workpiece poses. According to the visual identification method, 3D contour matching is carried out on the filtered workpiece point cloud and template point cloud of which the boundaries are extracted, so that the interference of a large amount of plane point clouds is reduced, and the matching precision is improved, and the calculation speed is increased.

Description

technical field [0001] The invention belongs to the field of machine vision, and more specifically relates to a visual recognition method, device, equipment and medium for unstacking of single items. Background technique [0002] In the field of industrial manufacturing and logistics, the traditional depalletizing system is realized based on deep learning image recognition and segmentation. The economic cost is high, and there are certain recognition errors. It is difficult to achieve accurate grasping and cannot adapt to the accuracy requirements for subsequent processing Scenes. In the palletizing scenario corresponding to depalletizing, high space utilization is required, the gap between adjacent items is small, and some even require close fit, which also requires depalletizing to have the ability to identify and divide items with small gaps. With the promotion of industrial-grade 3D cameras and the rise of 3D vision algorithms, the depalletizing system based on 3D visio...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention proposes a visual recognition method, device, equipment and medium for single-category unstacking, thereby solving the problem that the existing unstacking methods are affected by external ambient light. The quality of the picture is poor, and the position and size of the deep learning recognition may have a large deviation from the actual technical problem

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