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Inertial navigation system for an automatic guided vehicle with Mecanum wheels

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

Abstract

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.

Keywords

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

Nomenclature

L

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

W

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

Rw

wheel radius

νiw

linear velocity calculated from the rotation of the wheels

νir

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

νiX

linear velocity vector of each wheel along X-axis

νiY

linear velocity vector of each wheel along Y-axis

νX

linear velocity vector of X-axis of the AGV

νY

linear velocity vector of Y-axis of the AGV

ωz

angular velocity of the AGV

\(\dot \theta _i\)

angular velocity of the wheels

Δθi

angular variation of the wheels

φz

orientation of the AGV

Δφz

variation in the orientation of the AGV

ΔSX

variation of the position along X-axis

ΔSY

variation of the position along Y-axis

ΔνX

variation of the velocity vector along X-axis

ΔνY

variation of the velocity vector along Y-axis

uk

inputs of the Kalman filter

xk

process model

zk

measurement model

P

error covariance

Q

noise covariance of the process

R

noise covariance of the measurement

Gc

center value of an ADC for the gyro sensor

GADC

digital output of the gyro sensor

Tc

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

TADC

digital output of a temperature in a gyro sensor

ak

acceleration measured from an accelerometer on k-th

νk

velocity vector calculated from an accelerometer on k-th

Sk

position calculated from an accelerometer on k-th

wa

noise of an acceleration

wν

noise of a velocity

ws

noise of a position

dΔθ

error in the rotational speed of the wheels

dΔφ

error in the variation in the orientation of an AGV

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    Test Video of Sideway Drive, http://www.youtube.com/watch?v=hJgsoga28ao
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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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