@inproceedings{2f5883875c8a4fe5a658f21cae3556b8,
title = "Automatic assembly of eccentric shaft component based on the machine learning algorithm",
abstract = "An assembly strategy based on the machine learning algorithm is proposed to cope with the difficulties in the practical assembly of eccentric components in high-precision RV speed reducer. The simplified models of eccentric shaft hole are built to analyze the possible contact states in the process of assembly. Subsequently, the basic principles of the machine learning algorithm are introduced, and a shaft hole assembly method with supervised learning is put forward. At last, the platform for assembly robot is constructed and tested with force characteristic information, and the test results indicate the good effect of this assembly strategy.",
keywords = "Assembly robot, Force sensor., Machine learning, Shaft hole assembly",
author = "Zhang Jian and Hu Lei",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Computer Systems, Electronics and Control, ICCSEC 2017 ; Conference date: 25-12-2017 Through 27-12-2017",
year = "2018",
month = aug,
day = "24",
doi = "10.1109/ICCSEC.2017.8447035",
language = "英语",
isbn = "9781538635735",
series = "2017 International Conference on Computer Systems, Electronics and Control, ICCSEC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "806--809",
booktitle = "2017 International Conference on Computer Systems, Electronics and Control, ICCSEC 2017",
address = "美国",
}