Abstract
This paper presents positioning improvement of a laser navigation system (LNS) using unscented Kalman filter (UKF) for an automatic guided vehicle (AGV). The existing AGVs mainly used a magnetic system or an inductive system as a guidance system. However, those have high cost and difficult maintenance according to change of environment, and can drive only the designated path which sensors are installed on. The laser guidance system is developed to solve those problems, but it has also problems which is slow response time and low accuracy. Therefore, we propose a sensor fusion method for the AGV. The sensors used in this paper are encoders, a gyro and the LNS, and they are fused by UKF. To analyze the performance of the proposed system, we designed a fork-type AGV for ourselves, and performed the experiment that was repeated 5 times under the same working conditions. In experimental results, we verified that the proposed method could improve positioning accuracy of the LNS effectively. In addition, it was appropriate to apply a real AGV system for autonomous driving.
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Kim, J., Jung, K., Kim, J., Song, H., Kim, S. (2013). Positioning Accuracy Improvement of Laser Navigation Using Unscented Kalman Filter. In: Lee, S., Cho, H., Yoon, KJ., Lee, J. (eds) Intelligent Autonomous Systems 12. Advances in Intelligent Systems and Computing, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33926-4_77
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DOI: https://doi.org/10.1007/978-3-642-33926-4_77
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