Inertial navigation system for an automatic guided vehicle with Mecanum wheels

  • Jungmin Kim
  • Seungbeom Woo
  • Jaeyong Kim
  • Joocheol Do
  • Sungshin KimEmail author
  • Sunil Bae


This paper presents an INS (inertial navigation system) for an AGV (automatic guided vehicle) with Mecanum wheels. An omni wheel or a Mecanum wheel, which has rollers attached to a conventional wheel, facilitates omni-directional driving. Most positioning systems use the encoder because it can measure precisely the rotation of the wheel. However, it is difficult to accurately calculate the position of an AGV with omni wheels or Mecanum wheels because slips occur frequently in the rollers attached to the wheels. Therefore, many studies have been carried out to compensate for the weakness of the encoders by fusing an accelerometer and a gyro sensor. However, there is still a rapid increase in the number of errors, owing to the second integral of an accelerometer. Hence, this paper proposes an INS for an AGV with Mecanum wheels. The proposed system integrates an encoder, an accelerometer, and a gyro sensor through two Kalman filters. To verify the performance of the proposed INS, we analyzed the positioning accuracy of an AGV by studying straight, sideways, and diagonal movements over a 250 cm distance in a 300 cm × 300 cm space at speeds of about 200 and 380 mm/s. The results of the experiment showed that the proposed INS can measure effectively the position of an AGV, despite frequent slips.


Inertial navigation system Omni-directional Strapdown system Mecanum wheel Kalman filter 



distance between the centers of the AGV and the front or rear wheels


distance between the centers of the AGV and the left or right wheels


wheel radius


linear velocity calculated from the rotation of the wheels


actual linear velocity on the ground due to the rollers attached to wheels


linear velocity vector of each wheel along X-axis


linear velocity vector of each wheel along Y-axis


linear velocity vector of X-axis of the AGV


linear velocity vector of Y-axis of the AGV


angular velocity of the AGV

\(\dot \theta _i\)

angular velocity of the wheels


angular variation of the wheels


orientation of the AGV


variation in the orientation of the AGV


variation of the position along X-axis


variation of the position along Y-axis


variation of the velocity vector along X-axis


variation of the velocity vector along Y-axis


inputs of the Kalman filter


process model


measurement model


error covariance


noise covariance of the process


noise covariance of the measurement


center value of an ADC for the gyro sensor


digital output of the gyro sensor


center value of an analog to digital conversion temperature sensor in the gyro sensor


digital output of a temperature in a gyro sensor


acceleration measured from an accelerometer on k-th


velocity vector calculated from an accelerometer on k-th


position calculated from an accelerometer on k-th


noise of an acceleration


noise of a velocity


noise of a position


error in the rotational speed of the wheels


error in the variation in the orientation of an AGV


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Copyright information

© Korean Society for Precision Engineering and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jungmin Kim
    • 1
  • Seungbeom Woo
    • 2
  • Jaeyong Kim
    • 1
  • Joocheol Do
    • 1
  • Sungshin Kim
    • 1
    Email author
  • Sunil Bae
    • 3
  1. 1.School of Electrical EngineeringPusan National UniversityBusanSouth Korea
  2. 2.Department of Interdisciplinary Cooperative Course: RobotPusan National UniversityBusanSouth Korea
  3. 3.ATIS Corporation, B-501Ulsan Technopark Technical Innovation BuildingUlsanSouth Korea

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