Enhanced Real-Time Path Planning using Nonlinear Control for Unmanned Ground Vehicles

This study presents a comprehensive trajectory planning approach tailored for mobile robots. The primary objective is to achieve robust stability and real-time tracking of reference trajectories, with particular attention to maintaining dynamic stability limits and addressing disturbances encountered during trajectory execution. The proposed method leverages a potential field algorithm to enable precise trajectory tracking while ensuring effective obstacle avoidance. To validate the effectiveness of the approach, a series of experiments were conducted under realistic and dynamic conditions using the QBot-2e mobile robot. These experiments demonstrated the capability of the proposed method to achieve high-accuracy trajectory tracking, even in the presence of external disturbances. Additionally, the method’s adaptability to varying environments and its ability to maintain safe navigation paths further highlight its potential for real-world applications.