Comparative Analysis Between Pure Pursuit, Linear Quadratic Regulator and Stanley Controller for Ackermann Steering Drive in Gazebo

In this paper, three path-following control algorithms for autonomous vehicles are compared: Pure Pursuit, Linear Quadratic Regulator, and Stanley Controller, with Ackermann steering drive. The aim here is to determine the performance of these algorithms through three cardinal metrics: tracking accuracy, control smoothness, and computational time. All algorithms are compared within Gazebo simulator environment-a tested scenario simulating vehicle dynamics while passing through defined waypoints. This paper will discuss how closely each algorithm enables the vehicle to follow the intended path, the smoothness with which it carries out maneuvers without abrupt control changes, and the efficiency of the algorithm operation in terms of use of computational resources-which is, critical for real-time deployment into autonomous systems. The outcomes will be utilized to identify optimal path-tracking strategies for autonomous vehicles and hence inform the development of such efficient, robust control systems for practical applications.