Constrained Image-Based Visual Servoing using Barrier Functions

This paper presents a novel constrained image-based visual servoing (IBVS) approach that guarantees target features to remain within the camera field of view (FOV) for the duration of the task. Barrier function (BF) is used to transform the feature dynamics on the image plane into equivalent dynamics with full state constraints. An IBVS controller is designed for the full state constrained system that regulates the original system. A stability analysis is provided to prove the local asymptotic convergence of the state error in the sense of Lyapunov. Simulation and robot implementation results show the efficiency of the proposed method to reach the desired features from any initial configuration while the visibility constraints of the feature points are being realized.