Automatic Tuning Methodology of Visual Servoing System Using Predictive Approach

Cosmin Copot, Lei Shi, Steve Vanlanduit

Proc. IEEE International Conference on Control and Automation (ICCA), pp. 776–781, 2019.

Abstract

In this paper, a tuning methodology based on predictive model approach for visual servoing system is investigated. The proposed approach uses features prediction based method to estimate the camera velocity and thus to calculate the optimal control tuning parameter. In order to have a faster convergence and in the same time a desired behaviour of the servoing system, a new control parameter is computed every sampling time. To evaluate the designed tuning strategy, a visual servoing architecture with an eye-in-hand configuration has been considered. The experimental results showed that the proposed tuning algorithm based on prediction model has a stable and convergent behavior when dealing with visual servoing applications. To the knowledge of the authors, the proposed methodology is the first approach which enables an automatic selection of control parameter for the proportional visual control law.

Links

doi: 10.1109/ICCA.2019.8899522

BibTeX

@inproceedings{copot19_icca, author = {Copot, Cosmin and Shi, Lei and Vanlanduit, Steve}, title = {Automatic Tuning Methodology of Visual Servoing System Using Predictive Approach}, booktitle = {Proc. IEEE International Conference on Control and Automation (ICCA)}, year = {2019}, pages = {776--781}, doi = {10.1109/ICCA.2019.8899522} }