SCIENCE@home

Precise Measurement of Position and Attitude Based on Convolutional Neural Network and Visual Correspondence Relationship

Jiachen Yang,Jiabao Man,Meng Xi,Xinbo Gao,Wen Lu,Q. Meng

Published 2020 in IEEE Transactions on Neural Networks and Learning Systems

ABSTRACT

Accurate measurement of position and attitude information is particularly important. Traditional measurement methods generally require high-precision measurement equipment for analysis, leading to high costs and limited applicability. Vision-based measurement schemes need to solve complex visual relationships. With the extensive development of neural networks in related fields, it has become possible to apply them to the object position and attitude. In this paper, we propose an object pose measurement scheme based on convolutional neural network and we have successfully implemented end-to-end position and attitude detection. Furthermore, to effectively expand the measurement range and reduce the number of training samples, we demonstrated the independence of objects in each dimension and proposed subadded training programs. At the same time, we generated generating image encoder to guarantee the detection performance of the training model in practical applications.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-43 of 43 references · Page 1 of 1

CITED BY

Showing 1-19 of 19 citing papers · Page 1 of 1