Homography-Based Visual Servo Tracking Control of Wheeled Mobile Robots with Simultaneous Depth Identification

In this paper, a visual servo tracking control method is developed for the wheeled mobile robot subject to nonholonomic motion constraints, while the unknown feature depth information is simultaneously identified in the visual servoing process. Firstly, a video feature points are prerecorded as the desire trajectory for the mobile robot. Secondly, Euclidean homographies are constructed by utilizing projective geometric relationships of feature points. Subsequently, trajectory tracking errors are obtained after Euclidean homographies decomposition. Then, the kinematic controller is designed for the mobile robot to achieve the visual servo trajectory tracking task. Moreover, by utilizing the concurrent learning framework, the historical and current system data is used to construct an adaptive updating mechanism for recovering the unknown feature depth. Simulation results are collected to prove the efficiency and utility of the proposed strategy.