An overview of the robust approaches applied for 2D visual servoing

In this paper we present an overview of recent robust approaches which aim 2D visual servoing systems. Since Visual servoing has been considered as a very effective technique for positioning and tracking functionalities, its main goal was to find good selections of visual data in order to be injected in a closed-loop. To guarantee the visual servoing robustness, it is important to alter many techniques like extraction, matching, tracking and path planning. The robustness depends on the error minimization which means the ability to resist severe outliers and to analyze confidence in each feature. Thereby, we can accomplish a better control and an accurate robotic task.