@inproceedings{504f693ecf5f4d9985fc37adab59c4cf,
title = "Pose estimation of industrial objects towards robot operation",
abstract = "With the advantages of wide range, non-contact and high flexibility, the visual estimation technology of target pose has been widely applied in modern industry, robot guidance and other engineering practices. However, due to the influence of complicated industrial environment, outside interference factors, lack of object characteristics, restrictions of camera and other limitations, the visual estimation technology of target pose is still faced with many challenges. Focusing on the above problems, a pose estimation method of the industrial objects is developed based on 3D models of targets. By matching the extracted shape characteristics of objects with the priori 3D model database of targets, the method realizes the recognition of target. Thus a pose estimation of objects can be determined based on the monocular vision measuring model. The experimental results show that this method can be implemented to estimate the position of rigid objects based on poor images information, and provides guiding basis for the operation of the industrial robot.",
keywords = "Machine vision, Pose estimation, Robot guidance, Vision measurement, Visual guidance",
author = "Jie Niu and Fuqiang Zhou and Haishu Tan and Yu Cao",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Applied Optics and Photonics China: 3D Measurement Technology for Intelligent Manufacturing, AOPC 2017 ; Conference date: 04-06-2017 Through 06-06-2017",
year = "2017",
doi = "10.1117/12.2281939",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Asundi, \{Anand Krishna\} and Huijie Zhao and Wolfgang Osten",
booktitle = "AOPC 2017",
address = "美国",
}