Industrial part 6D pose estimation method and computer readable storage medium

Abstract

The invention provides an industrial part 6D pose estimation-oriented method and a computer readable storage medium. The method comprises the steps of determining a mapping function of a parameter value and a parameter key point and constructing a three-dimensional model library of limited number of size instances; based on the three-dimensional model library, generating a stacked data set throughsimulation of a physical engine and a rendering engine, and generating a parameter key point label and a parameter value label which are used for training a neural network provided by the technical scheme; predicting a spatial offset vector from each point to the mass center and parameter key points of the industrial part to which the point belongs; achieving individual segmentation of the stacking scene through a clustering algorithm, obtaining prediction centroids of individuals, classifying parameter key points of point-by-point prediction, obtianing prediction parameter key points and centroids of the individuals, then calculating point-by-point prediction parameter values, obtaining prediction parameter values of the individuals after classification, wherein the prediction parametervalues are used for calculating parameter key points and centroids of template instances; and obtaining a 6D pose estimation result through a least square fitting method.

Description

technical field [0001] The present invention relates to the technical field of pose estimation, in particular to a method for 6D pose estimation of industrial parts and a computer-readable storage medium. Background technique [0002] 6D pose estimation for industrial parts is an important research direction in the field of computer vision, and it is of great significance to promote the development of industrial intelligence and automation. With the rapid development of deep learning and computer vision related technologies, it has gradually become the mainstream research trend to solve the 6D pose recognition problem of industrial parts through deep learning networks. In practice, there are problems such as insufficient recognition efficiency, insufficient recognition accuracy, and insufficient network generalization ability. [0003] The 6D pose estimation for industrial parts refers to the prediction of the spatial position and attitude of scattered and diverse industria...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the existing problems, the present invention provides a method for 6D pose estimation of industrial parts and a computer-readable storage medium

Images