Motion Planning and Tracking Control of Unmanned Ground Vehicle Based on 3D Lidar Data
This paper addresses the problem of path planning and tracking control of the Unmanned Ground Vehicle (UGV) with a special focus on control tracking algorithms. The objectives of the research are the implementation, analysis, and comparison of different control strategies: PID, Stanley and Pure Pursuit. The implementation was carried out using the Robot Operating System (ROS) and the Gazebo simulator on the xMachines x100 UGV robot. Through a series of simulation experiments, the performance of the controllers was evaluated by employing a positioning error metrics, heading error and cross-track error. The obtained results indicated that the PID controller achieves the best performance regarding path tracking accuracy, while the Stanley and Pure Pursuit controllers obtain larger deviations, particularly pronounced in the final movement segment. Although the Stanley controller enabled faster task execution and the Pure Pursuit ensured smoother movement, the PID controller proved to be the most reliable solution. This paper provides a systematic insight into the practical application of these algorithms and guidelines for selecting an adequate controller depending on specific requirements.