STATE ESTIMATION FOR AUTONOMOUS GUIDED VEHICLE USING THE EXTENDED KALMAN FILTER
Jaeyoon Junga, Hansil Kima, Kyungsup Parka, and Kwang Y. Leeb
a Department of Electrical Engineering, The University of Ulsan, Korea 680-749
b Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, U.S.A
This paper presents a four-wheel drive autonomous guided vehicle (AGV) system designed to transport unmanned control transportation (UCT) standard cargo containers in seaport environments. A model vehicle is simulated and experimented in laboratory and in a prepared road at speed up to 3 meters per sec. The navigation system is based on the use of encoder, gyro, and transponders at known locations in the environment. A general method for the construction of a positioning system is proposed, which is based on an extended Kalman filter (EKF) and commercially available navigation sensors in an absolute coordinate of AGV. The kinematics model and observation models are adapted for EKF application. Simulation result shows good performances of the AGV state estimator.
Keywords: Extended Kalman filter, Autonomous Guided Vehicle, Unmanned Control Transportation, state estimator, encoder, transponder
Session slot T-Th-E21: Posters of Transportation and Vehicles/Area code 8f : Intelligent Autonomous Vehicles

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