Localization Based on Matching Location of Agv

Localization is a critical issue in mobile vehicles. Mobile vehicles must know its position and orientation in order to movement to reach the goals precisely. In this paper, we describe localization techniques for AGV that is based on the principle of Kalman Filtering (KF) algorithm estimation. This paper addresses the problems of factory navigation and modelling with focus on keeping automatic travelling along the control path of the AGV. AGV path is generated by cubic polynomial trajectory and stored in memory. Position and orientation is measured by using encoder sensor on driving and steering axes. We develop the control and localization system. Reference path and observation measurement are matched. To keep track of the matching result of both positions, the estimated location information used to update the vehicle’s position by using the Kalman Filtering (KF) algorithm. The proposed algorithm is verified by simulation using Matlab software and implemented on PLC TSX micro from SCHNEIDER. The implemented program is written by PL7 Pro using Grafcet techniques.