Model predictive control-based path tracking control for automatic guided vehicles

Abstract

In this study, a path tracking control method based on model predictive control (MPC) is presented to improve the results of path tracking. A simulation model of an automatic guided vehicle (AGV) is employed in a robot operating system (ROS). A collision free path is established with the ROS under the scene of continuous turning as a reference path. A linear MPC controller is used to control the AGV in the ROS, and a simulation experiment is performed with the combined simulation of ROS and MATLAB. Experimental results verify that the proposed MPC controller has a good tracking performance under complex road conditions.