Abstract
In this paper, an analytical method of robot error model based on multi-vision measurement system and a scheme about step-by-step calibration of robot angle and position error in the measuring space are introduced. This paper analyzes the calibration method of vision measuring system, and the transformation error model between robot coordinate system and vision coordinate system is discussed. The kinematic parameter error model of robot for each axis and the error model of the target at the end of robot caused by mechanical installation are established. According to these error models, the coordinate system transformation error, kinematic parameter error, target mechanical installation error contributing to the angle error and position error of robot are calibrated in step, and in consequence. The calibration accuracy of position and angle error for robot is improved obviously. Experiments verify that the calibration method in multi-vision measuring space that is proposed in the paper has an excellent effect on improving the robot motion control precision.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang, T., Dai, X.-L.: Kinematic calibration of robot based on distance error. J. South China Univ. Technol. (Nat. Sci. Ed.) 39(11), 98–103 (2011)
Xie, Z., Xin, S., Li, X.: Method of robot calibration based on monocular vision. J. Mech. Eng. 47(5), 35–39 (2011)
Santolaria, J., Gine, M.: Robotics and computer-integrated manufacturing. Robot. Comput.-Integr. Manuf. 29, 370–384 (2013)
Gao, W., Wang, H., Jiang, Y.: A calibration method for serial robots based on POE formula. Robot 35(2), 156–161 (2013)
Zhong, X., Lewis, J., N-Nagy, F.: Inverse robot calibration using artificial neural networks. Eng. Appl. Artif. Intell. 9(1), 83–93 (1996)
Shamma, J.S., Whitney, D.E.: A method for inverse robot calibration. Trans. ASME 109(1), 36–43 (1987)
Alici, G., Shirinzadeh, B.: A systematic technique to estimate positioning errors for robot accuracy improvement using laser interferometry based sensing. Mech. Mach. Theor. 40(8), 879–906 (2005)
Huang, G.: Study on the key technologies of digital close range industrial photogrammetry and applications. Tianjin: Tianjin University (2005)
Jie, X.U.: Analyzing and improving the tsai camera calibration method in machine vision. Comput. Eng. Sci. 32(4), 45–48 (2010)
Li, H., Wang, J.I.: A research on camera calibration technique. Optical Instrum. 29(4), 7–12 (2007)
Fang, H., Liu, X.: Parameter determination in robot kinematic model. J. Mach. Des. 28(2), 46–49 (2011)
Sun, M., Ren, L., Han, H.: Series robot tracking detection system based on stereo vision. Comput. Eng. 28(13), 240–243 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Li, R., Wang, B., Zhao, Y. (2019). A Study on Step-by-Step Calibration of Robot Based on Multi-vision Measurement. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11744. Springer, Cham. https://doi.org/10.1007/978-3-030-27541-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-27541-9_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27540-2
Online ISBN: 978-3-030-27541-9
eBook Packages: Computer ScienceComputer Science (R0)