Unified Tracking and Regulation Visual Servoing of Wheeled Mobile Robots With Euclidean Reconstruction

In this paper, a vision-based approach is proposed for the unified tracking and regulation task of a wheeled mobile robot equipped with a monocular camera. To construct the error system, the orientation and scaled position information is extracted from the current, the reference, and the desired images based on the homography techniques. Considering the nonholonomic constraint and the unknown depth constant, an adaptive continuous controller is designed to address both the trajectory tracking and the regulation problems using visual feedback. The Lyapunov-based stability analysis is exploited to prove that the proposed controller can achieve asymptotic tracking and regulation in the presence of the system uncertainties. The proposed approach is model-free, and the selection of the control gains is flexible without any additional constraint. Moreover, an update law is designed to estimate the unknown depth constant. Provided that a persistent excitation condition is satisfied, the estimate of the depth constant will converge to the actual value, and then the Euclidean space can be reconstructed. Simulation results are provided to validate the effectiveness of the proposed approach.