Trajectory Tracking for Autonomous Vehicle: Design and Implementation

This research presents an integrated approach for trajectory tracking of autonomous vehicles using the advanced control techniques of linear quadratic regulator (LQR) and state-of-the-art sensors and technologies such as IMU, LiDAR, SLAM, and ROS. The proposed approach utilizes these control techniques and sensors to perform real-time localization, mapping, and predefined trajectories for the vehicle. The tracking component of the system utilizes the motion commands generated by the path planner and the sensor data to ensure the car follows the path accurately and robustly. The proposed approach is evaluated using simulations and experiments with actual autonomous vehicles. The results show the effectiveness of the proposed method in improving the performance of autonomous vehicles in terms of safety, accuracy, and efficiency by combining different techniques to obtain a stable and efficient solution.