This paper proposes a robust tracking controller based on a Generalized Extended State Observer (GESO) method for a wheeled mobile robot (WMR) with unknown skidding and slipping. Skidding and slipping of a WMR are inevitable in practice. We regard skidding and slipping as disturbances and modify the dynamics model to consider them simply. Then, we adopt the GESO to design a robust tracking controller at kinematic and dynamic level. Using Lyapunov theory, we derive the control law and guarantee the stability of the control system. The proposed control achieves attenuation of the disturbance and convergence of the tracking errors. The performance of the proposed method is verified by some simulation results.

We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird’s eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

This paper represents a robust backstepping tracking control based on a Lyapunov redesign for Skid-Steered Wheeled Mobile Robots (WMRs). We present kinematic and dynamic models that explicitly relate the perturbations to the skidding in order to improve the tracking performance during real running. A robust controller is synthesized in the backstepping approach and the Lyapunov redesign technique, which forces the error dynamics to stabilize to the reference trajectories. We design an additional feedback control - a Lyapunov redesign - such that the overall control stabilizes the actual system in the presence of uncertainty and perturbation with the knowledge of the Lyapunov function. Simulation results are provided to validate and analyse the performance and stability of the proposed controller.

This paper proposes a robust tracking controller based on the Fuzzy Disturbance Observer (FDO) for a Wheeled Mobile Robot (WMR) with unknown skidding and slipping. The proposed method provides disturbance-free techniques for stability analysis. In our previous work [ 1 ], we proposed an extended state-observer approach to robust tracking control for wheeled mobile robots with skidding and slipping. Even though satisfying performances were shown and the proposed method was verified in [ 1 ], the derivatives of disturbance should go to zero as time passes in order to guarantee performance. This is a very critical assumption. The method proposed in this paper overcomes this problem using universal approximation with a fuzzy model. Thus, the condition that disturbance should disappear with time is not required anymore. Furthermore, the proposed method can be used more widely than that shown in the previous work. This is guaranteed by a Lyapunov-theory-based stability analysis, and performance is verified by simulation results.