Adaptive visual servoing using angle and distance

This paper presents a novel adaptive controller for image-based visual servoing of robots with an eye-in-hand camera using angle and distance features. The key idea lies in the development of the depth-independent interaction matrix and the proposal of an adaptive algorithm for estimating the unknown geometric parameters of the features in the 3-D space. The Lyapunov theory is used to prove the asymptotic convergence of the image error to zero based on the nonlinear robot dynamics. Finally, experiments have been conducted to demonstrate the performance of the proposed approach.