A Workpiece Pose Estimation Method Based on Component Model Expression

Abstract

The invention discloses a workpiece pose estimation method based on component model expression, comprising the following steps: performing data enhancement on the data to be detected, and obtaining processed images; performing feature extraction on the images through a convolutional neural network, and obtaining three scales Feature map; each feature map expresses the network structure through the component model, and obtains the corresponding scores and model response maps of the whole and parts; optimizes the parameters of all model response maps to obtain a comprehensive response map and key points; calculates n in the space through the EPnP algorithm A 3D point is matched with a 2D point in the image to obtain the corresponding pose of the camera. The invention only needs to mark the information of the workpiece as a whole, uses the component information of the workpiece as a hidden feature, and automatically finds effective components through the neural network to mark the components, has fast and efficient performance, and can calculate weak textures such as workpieces in real time and accurately Advantages of the 6D pose of the object.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a workpiece pose estimation method based on component model expression. Background technique [0002] In practical applications, it is very critical to obtain the 3D information of the target object. For example, in the task of manipulator grasping manipulation, recognizing the 6D pose (3D positioning and 3D orientation) of an object provides useful information for grasping and motion planning. The difficulty of estimating the pose of a workpiece is that the workpiece is a weakly textured object, which is easily affected by light and reflection, so that the texture reflected from the 2D image may not be the real texture of the 3D object surface. Moreover, when the resolution of the image changes, the calculated texture may have a large deviation, and the feature extraction algorithm is not easy to identify. In the actual process of pose estimation, there are still objective facto...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a workpiece pose estimation method based on component model expression, which solves the problem that the existing methods cannot handle weak texture objects such as workpieces well, cannot accurately estimate the pose of workpieces, and have low adaptability The problem

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