Stability and Convergence Analysis of 3D Feature-Based Visual Servoing

Visual control based on image features has received much attention for its inherent robustness against camera calibration errors, modelling uncertainties and the capability to keep object in Field of View (FoV) camera. Nevertheless, some drawbacks related basin convergence existence local minima, which make get stuck undesired equilibrium points, are still worth being investigated. Nowadays, availability cheap lightweight RGB-D cameras makes use three-dimensional natural. By using an eye-in-hand configuration, this letter proposes in-depth stability analysis 3D feature-based visual servoing. It will be proved that system is almost globally asymptotically stable sense only trajectories not converging desired point those belonging a zero Lebesgue measure set feature space. Moreover, sufficient condition guaranteeing remain FoV derived algorithm prevent loss caused by violation constraint proposed.