Positioning Accuracy Improvement of Laser Navigation Using Unscented Kalman Filter

  • Jungmin Kim
  • Kyunghoon Jung
  • Jaeyong Kim
  • Hajun Song
  • Sungshin Kim
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 193)


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.


unscented Kalman filter laser navigation automatic guided vehicle 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jungmin Kim
    • 1
  • Kyunghoon Jung
    • 1
  • Jaeyong Kim
    • 1
  • Hajun Song
    • 1
  • Sungshin Kim
    • 1
  1. 1.Dept. of Electrical EngineeringPusan National UniversityGeumjeongKorea

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