Dynamic performance improvement of direct image-based visual servoing in contour following

Abstract

Image-based visual servoing (IBVS) has increasingly gained popularity and has been adopted in applications such as industrial robots, quadrotors, and unmanned aerial vehicles. When exploiting IBVS, the image feature velocity command obtained from the visual loop controller is converted to the velocity command of the workspace through the interaction matrix so as to converge image feature error. However, issues such as the noise/disturbance arising from image processing and the smoothness of image feature command are often overlooked in the design of the visual loop controller, especially in a contour following task. In particular, noise in the image feature will contaminate the image feedback signal so that the visual loop performance can be substantially affected. To cope with the aforementioned problem, this article employs the sliding mode controller to suppress the adverse effects caused by image feature noise. Moreover, by exploiting the idea of motion planning, a parametric curve interpolator is developed to generate smooth image feature commands. In addition, a depth observer is also designed to provide the depth information essential in the implementation of the interaction matrix. In order to assess the feasibility of the proposed approach, a two-degrees-of-freedom planar robot that employs an IBVS structure and an eye-to-hand camera configuration is used to conduct a contour following task. Contour following results verify the effectiveness of the proposed approach.