Part identification and positioning method based on mixed model

A hybrid model and part technology, applied in image data processing, instruments, calculations, etc., can solve the problems of discrete translation and rotation accuracy, geometric deformation of parts and template images, and low recognition and positioning accuracy of template matching algorithms, and achieve robustness. High and robust effect

Inactive Publication Date: 2018-03-20
CHUZHOU UNIV
View PDF6 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, on the one hand, this algorithm can only obtain discrete translation and rotation accuracy; on the other hand, under conditions such as camera viewing angle changes, nonlinear lighting changes, occlusion or cluttered backgrounds, there are often geometric deformations in parts and template images
The above two reasons lead to low positioning accuracy of template matching algorithm

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Part identification and positioning method based on mixed model
  • Part identification and positioning method based on mixed model
  • Part identification and positioning method based on mixed model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] In order to further illustrate the features of the present invention, please refer to the following detailed description and accompanying drawings of the present invention. The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present invention.

[0046] Such as figure 1 As shown, this embodiment discloses a hybrid model-based part identification and positioning method, including the following steps S1-S5:

[0047] S1. Collect the part image, and use the template matching algorithm to identify the parts in the part image, and obtain the corresponding pose of each part;

[0048] It should be noted that, in this embodiment, the model MV120SC produced by Vision Vision Company is used to collect images with an industrial camera with an imaging resolution of 1280 pixels × 960 pixels and a focal length of 8 mm. The collected images are as follows: figure 2 shown. Then create template image like image ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention discloses a part identification and positioning method based on a mixed model, belonging to the field of image processing technology. The method comprises the steps of: S1, collecting part images, identifying parts in the part images by employing a template matching algorithm, and obtaining one pose corresponding to each part; S2, extracting one edge point set of each identified part, and extracting an edge point set of a template image and a direction vector thereof; S3, based on a Gaussian mixture model, constructing one likelihood function of geometrical errors betweeneach part edge point set and the edge point set of the template image; S4, employing an EM algorithm to perform optimization of the constructed likelihood functions, and obtaining optimal values of the geometrical errors; and S5, employing the optimal values of the geometrical errors to perform correction of the poses of the corresponding parts, obtaining one corrected pose of each part, and identifying each part in the part images. The part identification and positioning method based on the mixed model has accurate identification and positioning effects and has good robustness.

Description

technical field [0001] The invention relates to the technical field of visual industrial robots, in particular to a part recognition and positioning method based on a hybrid model. Background technique [0002] Industrial robot is a comprehensive integration of key technologies such as mechanical mechanism, motion planning and control system. It has the advantages of high work efficiency, stability and reliability, and good repeatability. It is widely used in welding, palletizing, assembly, processing, testing, logistics handling and spraying. It plays an important role in the transformation and upgrading of labor-intensive industries. In 2014, the sales volume of industrial robots in my country was 57,000 units, which has become the world's largest industrial robot market. In 2015, the "Made in China 2025" issued by the State Council proposed to accelerate the development of intelligent equipment and vigorously encourage the development of industrial robot technology. At p...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/30G06T7/13
CPCG06T7/001G06T2207/10004G06T2207/30164G06T7/13G06T7/30
Inventor 张青林桂潮王波苏金文
Owner CHUZHOU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap