ABSTRACT
This chapter proposes the vision-based approach to address the unified tracking and regulation problem of the wheeled mobile robot. It presents an approach for the unified tracking and regulation visual serving of the wheeled mobile robot. Exploiting the homography-based techniques, the orientation and scaled position information used in the error system is extracted from the current, the reference, and the desired images. An adaptive continuous controller is developed by fully taking the nonholonomic constraint and the unknown depth constant into consideration. Once the unknown depth constant is identified, the Euclidean space can be reconstructed. The asymptotic stability of the error system is proven via the Lyapunov-based analysis. The Lyapunov-based method is utilized to prove the asymptotic stability of the control system. The performance of the proposed vision-based unified tracking and regulation approach is evaluated from the simulation results.
