A Robust Design for Image-based Visual Servoing

In this paper we introduce a new robust visual scheme intended to 2D visual servoing robotic tasks. The main object is to direct the robot to its desired position. To be able to carry out such a task robustly the tough and major step is primarily the image processing procedure. We should find good selections of visual data in order to be correctly matched and interpreted by the visual control law regardless of the different sorts of errors. The new proposed design combines the speed up robust features (SURF) algorithm and progressive sample consensus (PROSAC) algorithm to accomplish a good feature extraction and to rapidly resist the environment constraints while removing the erroneous matches.

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