This paper presents the design and implementation of a mobile relay robot based on a differential wheeled platform. Tube Model Predictive Control (Tube-MPC) scheme is applied for precise and robust trajectory tracking under system disturbances and mod...
This paper presents the design and implementation of a mobile relay robot based on a differential wheeled platform. Tube Model Predictive Control (Tube-MPC) scheme is applied for precise and robust trajectory tracking under system disturbances and modeling uncertainties. The hardware adopts a compact and lightweight design, enabling stable integration of the communication and control modules within a single platform. The robot employs an board of repeater to establish a mesh network connection, while the control board and actuators form the driving and control system. Sensors and actuators communicate through serial(UART) interfaces, ensuring reliable data exchange between modules. The proposed control framework constructs an error set bounded by the maximum position error between the nominal and actual systems, forming a robust tube set that approximates the infinite-horizon disturbance-invariant set. This structure enables the controller to maintain the system trajectory within a guaranteed tube region while preserving robustness against disturbances. When an initial position error occurs, slow convergence can arise; however, by defining a reference error matrix, the conventional cost function is reformulated as a tracking optimization problem, which improves convergence speed and reduces tracking error. The optimization cost explicitly penalizes control effort and state deviations to ensure stability and constraint satisfaction within the feasible region. Simulation results demonstrate that the proposed Tube-MPC algorithm achieves higher tracking accuracy, faster convergence, and shorter tube contraction time compared with conventional MPC and Tube-MPC methods. Furthermore, experimental validation on the developed relay robot platform confirms the reliability and real-time feasibility of the proposed control system in indoor environments.