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A Human-Guided Vision-Based Measurement System for Multi-Station Robotic Motion Platform Based on V-Rep

Published online by Cambridge University Press:  27 September 2019

Yabin Ding*
Affiliation:
Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300354, China. E-mails: ybding@tju.edu.cn, 1837825836@qq.com, zhenjunluo@tju.edu.cn
Wei Guo
Affiliation:
Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300354, China. E-mails: ybding@tju.edu.cn, 1837825836@qq.com, zhenjunluo@tju.edu.cn
Xianping Liu
Affiliation:
School of Engineering, University of Warwick, Coventry, UK. E-mail: X.Liu@warwick.ac.uk
Zhenjun Luo
Affiliation:
Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300354, China. E-mails: ybding@tju.edu.cn, 1837825836@qq.com, zhenjunluo@tju.edu.cn
*
*Corresponding author. E-mail: ybding@tju.edu.cn
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Summary

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In the manufacturing process of sophisticated and individualized large components, classical solutions to build large machine tools cannot meet the demand. A hybrid robot, which is made up of a 3 degree-of-freedom (3-DOF) parallel manipulator and a 2-DOF serial manipulator, has been developed as a plug-and-play robotized module that can be rapidly located in multi-stations where machining operations can be performed in situ. However, processing towards high absolute accuracy has become a huge challenge due to the movement of robot platform. In this paper, a human-guided vision system is proposed and integrated in the robot system to improve the accuracy of the end-effector of a robot. A handheld manipulator is utilized as a tool for human–robot interaction in the large-scale unstructured circumstances without intelligence. With 6-DOF, humans are able to manipulate the robot (end-effector) so as to guide the camera to see target markers mounted on the machining datum. Simulation is operated on the virtual control platform V-Rep, showing a high robust and real-time performance on mapping human manipulation to the end-effector of robot. And then, a vision-based pose estimation method on a target marker is proposed to define the position and orientation of machining datum, and a compensation method is applied to reduce pose errors on the entire machining trajectory. The algorithms are tested on V-Rep, and the results show that the absolute pose error reduces greatly with the proposed methods, and the system is immune to the motion deviation of the robot platform.

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Type
Articles
Copyright
© Cambridge University Press 2019