Global Posture Stabilization for the Kinematic Model of a Rear-Axle Driven Car-Like Mobile Robot Considering Obstacle Avoidance

The car-like mobile robot (CLMR) is a kind of wheeled robot that has many applications in industry, transportation, security, etc. The CLMR considered in this study has rear-wheel driving. The robot is subject to nonholonomic constraints, and the robotic system is classified as a nonlinear and underactuated system. These characteristics increase the control design challenge. Few studies have focused on the global posture stabilization problem of CLMR and even fewer studies have considered obstacle avoidance. In this study, we designed two posture stabilization controllers. Controller 1 is globally asymptotically stable. We provide rigorous mathematical justifications of convergence using the proof by contradiction and Barbalat's lemma. Considering obstacle avoidance, Controller 2 can converge errors to arbitrarily small values. To the best of our knowledge, there is no global posture stabilization controller for CLMR in the existing literature. To prove the merit of the proposed controllers, we compared them with a controller from a well-known previous research through computer simulations. Experimental results confirmed the functionality of the proposed controller in a real-world situation.