Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)

Machine Vision Calibration of High Precision Platform Based on Adaptive Grid Method

Authors
Zhiqiang Kang, Jinchi Bai, Han Li
Corresponding Author
Zhiqiang Kang
Available Online August 2018.
DOI
10.2991/caai-18.2018.13How to use a DOI?
Keywords
high-precision robot; three driving modules; adaptive grid method; high efficiency
Abstract

The main purpose of this paper is to study the location calibration of 3-PPR high precision robot platform. The conventional precision calibration method has certain limitations, This paper adopts adaptive grid method for machine vision calibration, When the precision requirements are met, the mesh is reduced to continue calibration until the requirements are met. Otherwise automatically adjust the plane and continue to calibrate. The experimental results show that the adaptive mesh method has better performance than other methods, To meet the requirement of position calibration of 3D precision working platform with common plane.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
August 2018
ISBN
10.2991/caai-18.2018.13
ISSN
2589-4919
DOI
10.2991/caai-18.2018.13How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhiqiang Kang
AU  - Jinchi Bai
AU  - Han Li
PY  - 2018/08
DA  - 2018/08
TI  - Machine Vision Calibration of High Precision Platform Based on Adaptive Grid Method
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 54
EP  - 57
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.13
DO  - 10.2991/caai-18.2018.13
ID  - Kang2018/08
ER  -