Control of a Two-wheeled Self-balancing Robot With a Sliding Mechanism

Abstract

Two-wheeled self-balancing robot maintains balance and performs driving functions using two wheels, featuring excellent mobility due to its simple structure and wheel-driven system. However, when a long longitudinal structure is applied to increase space efficiency, challenges may arise in balance control and slope entry. In this study, a sliding mechanism and Model Predictive Control (MPC) were applied to achieve balance and driving control for a robot with a long longitudinal body. The system dynamics were analyzed using the Lagrangian method, and a reference for the sliding mechanism was generated to support balance control. Through Gazebo simulations, the performance of the MPC algorithm was verified, confirming that the robot could reach a stable balance state through Swing-up motion and maintain balance consistently. Additionally, stable driving performance was demonstrated in slope driving tests. We conducted experiments by applying the same algorithm to the actual robot, confirming that it successfully performed stable balance control and slope driving control in real-world environments.