Advanced Robotics and Automated Systems (ARAS), Industrial Control Center of Excellence (ICEE), Faculty of Electrical and Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran
Advanced Robotics and Automated Systems (ARAS), Industrial Control Center of Excellence (ICEE),
The performance of visual servoing systems can be enhanced through nonlinear controllers. In this paper, a sliding mode control is employed for such purpose. The controller design is based on the outputs of a pose estimator which is implemented on the scheme of the position-based visual servoing (PBVS) approach. Accordingly, a robust estimator based on unscented Kalman observer cascading with Kalman filter is used to estimate the position, velocity and acceleration of the target. Therefore, a PD-type sliding surface is selected as a suitable manifold. The combination of the estimator and nonlinear controller provides a robust and stable structure in PBVS approach. The stability analysis is verified through Lyapunov theory. The performance of the proposed algorithm is verified experimentally through an industrial visual servoing system.