Fast parking control of mobile robots: a motion planning approach with experimental validation

This paper presents a solution to the general parking problem of nonholonomic mobile robots based on motion planning and tracking controller design. A new global tracking controller is first proposed to achieve global uniformly asymptotic stability and local exponential convergence. The parking problem is then transformed into a tracking one by adding a redesigned virtual trajectory to the original trajectory, thus guaranteeing practical stability with exponential convergence. Further improvement in parking performance is obtained through linearization and pole-placement methods. One feature of our approach is that fast convergence in parking and tracking can be treated at the same time without switching between two controllers. Moreover, a tuning function is used to enhance parking performance. With the proposed framework, various tracking controllers given in the literature can be adopted to handle parking problems. The effectiveness of the proposed methods is verified by several interesting experiments including parallel parking and back-into-garage parking.