Estimation and Control of an Automated Guided Vehicle

In this paper a control strategy of Automated Guided Vehicle (AGV) is proposed. The vehicle movement controlled by an inboard PLC do not need physical guide. The vehicle has 3 wheels. The front wheel is used for steering and driving. The 2 rear wheels are free and equipped with 2 encoders. The strategy is based on 2 main purposes: the path is stored in the PLC memory and the vehicle displacement is calculated form the wheel rotation measurement. The comparison between the required path and the actual position of the AGV allow calculating deviation error. Function of this error, a correction strategy of driving speed and steering angle is applied in order to get a smooth and precise displacement. Mobile vehicles must know its position and orientation in order to movement to reach the goals precisely. We describe localization techniques for AGV that is based on the principle of Kalman Filtering (KF) algorithm estimation. This paper also addresses the problems of factory navigation and modelling with focus on keeping automatic travelling along the control path of the AGV. Position and orientation is measured by using encoder sensor on driving and steering axes. The control and localization systems are developed. Reference path and observation measurement are matched. To keep track of the matching result of both positions, the estimated position information used to update the vehicle’s position by using the Kalman Filtering (KF) algorithm. Test performance is verified with accurate positioning control by simulation and experimentation. Keyword: Automated Guided Vehicle (AGV), Controlled Path, Kalman Filter Estimator, PID controller