An Optimized Control Strategy for Image-Based Visual Servoing Using Polar Coordinates

Abstract

Image-based visual servoing is a crucial technique in robotic systems that enables accurate manipulation and control through visual feedback. In scenarios involving substantial rotational motion or changes in orientation, traditional Cartesian-based visual servoing methods may encounter limitations in terms of control performance. To address this challenge, we propose a novel approach that use coordinates for visual servoing control. By reparametrizing the control inputs in terms of polar radius and polar angle, our method offers a more intuitive and efficient way to handle rotations and angular variations. In addition, we further study the polar-based IBVS control by conducting experiments using a Proportional (P) controller as well as the Levenberg-Marquardt (LM) algorithm respectively, and the experimental results indicate that the proposed method demonstrates a faster convergence speed and better robustness.