• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.132-138
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• 2014

The use of AGVs(Automated Guided Vehicles) are increasing in many factories. The most widely used AGV system is that magnetic tapes are attached on the factory floor to make guided path and an AGV equipped with a magnetic sensor follows the path by sensing magnetic flux. In this AGV system, usually a magnetic sensor is attached on the front end of an AGV to detect the guided path and the sensor generates analog voltages proportional to the magnetic flux. The problem is that the AGV in use has rather big tracking errors because the accurate orientation of the AGV can not be detected by using only one magnetic sensor. In this paper, we propose a method to minimize the path tracking errors. In our method, one additional sensor is attached on the rear end of the AGV to estimate the orientation of the AGV and to control more accurately the AGV according to the estimated orientation of the AGV. We performed several experiments and the results successfully show the feasibility of the proposed method.

• Journal of Sensor Science and Technology
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• v.10 no.2
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• pp.134-141
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• 2001

This paper describes a method to steer an autonomous electric vehicle using magnetic fields. Magnets are embeded along the center of the road and a magneto-resistive sensor is mounted beneath the front bumper of the vehicle. As the vehicle moves along the road neural network controller controls the vehicle using measured magnetic field variation. Based on a single magnets modeling equation, we analyzed three dimensional magnetic field distributions of embeded magnets in series on the center of the road and performed a computer simulation using this results. In simulation study, straight and curved road was configured. The steering controller for the vehicle was designed using neural network and experiment was performed on the real embeded magnets using real autonomous electric vehicle. At the experiment we compensated the earth's magnetic fields and showed a good result driving an autonomous vehicle using proposed method.