Enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic

Visual servoing is a commonly employed approach in robotics and unmanned aerial vehicles (UAVs) that facilitates accurate object positioning and movement control by utilizing visual feedback. As quadrotors gain popularity, more control methods have been developed. This article presents a method for enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic. Unlike traditional visual servoing, which relies on a fixed gain and often encounters challenges with velocity convergence and maintaining the object in the field of view, this method is designed to enhance the visual servo control of quadrotors by dynamically adjusting the gain of the IBVS system through a fuzzy logic controller. This controller adaptively adjusts the servo gain in response to feature errors and the depth of the object's feature points. MATLAB simulations clearly demonstrate the superior performance of this fuzzy logic integrated method compared to classical approaches, showcasing enhanced control capabilities in challenging environments.