Regular Papers

International Journal of Control, Automation and Systems 2020; 18(5): 1324-1334

Published online November 28, 2019

https://doi.org/10.1007/s12555-018-0753-y

© The International Journal of Control, Automation, and Systems

Adaptive Switch Image-based Visual Servoing for Industrial Robots

Ahmad Ghasemi, Pengcheng Li, and Wen-Fang Xie*

Concordia University

Abstract

In this paper, an adaptive switch image-based visual servoing (IBVS) controller for industrial robots is presented. The proposed control algorithm decouples the rotational and translational camera motions and decomposes the IBVS control into three separate stages with different gains. This method can increase the system response speed and improve the tracking performance of IBVS while the proposed adaptive law deals with the uncertainties of the monocular camera in eye-in-hand configuration. The stability of the designed controller is proved using Lyapunov method. Experimental results on a 6 degree of freedom (DOF) robot show the significant enhancement of the control performance over other IBVS methods, in terms of the response time and tracking performance. Also the designed visual servoing controller demonstrates its capability to overcome some of the inherent drawbacks of IBVS, such its inability to perform a 180◦ camera rotation around its center.

Keywords Adaptive control, image-based visual servoing, industrial robots, switch control.

Article

Regular Papers

International Journal of Control, Automation and Systems 2020; 18(5): 1324-1334

Published online May 1, 2020 https://doi.org/10.1007/s12555-018-0753-y

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Switch Image-based Visual Servoing for Industrial Robots

Ahmad Ghasemi, Pengcheng Li, and Wen-Fang Xie*

Concordia University

Abstract

In this paper, an adaptive switch image-based visual servoing (IBVS) controller for industrial robots is presented. The proposed control algorithm decouples the rotational and translational camera motions and decomposes the IBVS control into three separate stages with different gains. This method can increase the system response speed and improve the tracking performance of IBVS while the proposed adaptive law deals with the uncertainties of the monocular camera in eye-in-hand configuration. The stability of the designed controller is proved using Lyapunov method. Experimental results on a 6 degree of freedom (DOF) robot show the significant enhancement of the control performance over other IBVS methods, in terms of the response time and tracking performance. Also the designed visual servoing controller demonstrates its capability to overcome some of the inherent drawbacks of IBVS, such its inability to perform a 180◦ camera rotation around its center.

Keywords: Adaptive control, image-based visual servoing, industrial robots, switch control.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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