Trajectory Estimation of a Tracked Mobile Robot Using the Sigma-Point Kalman Filter with an IMU and Optical Encoder

  • Xuan Vinh Ha
  • Cheolkeun Ha
  • Jewon Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)


Trajectory estimations of tracked mobile robots have been widely used to explore unknown environments and in military applications. In this paper, we estimate the precise trajectory of a tracked skid-steered mobile robot that contains an inertial measurement unit (IMU) and an optical encoder. For a systematic estimation, we implement a sigma-point Kalman filter (SPKF), which produces more accurate trajectory information, is easier to calculate, and requires no analytic derivations or Jacobians. The proposed SPKF compensates for the limitations of the IMU and encoder in trajectory estimation problems, as observed from our experimental results.


Tracked mobile robots Inertial Measurement Unit (IMU) Sensor fusion Sigma-Point Kalman Filter (SPKF) 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xuan Vinh Ha
    • 1
  • Cheolkeun Ha
    • 1
  • Jewon Lee
    • 2
  1. 1.School of Mechanical EngineeringUniversity of UlsanRepublic of Korea
  2. 2.Prigent Ltd.Republic of Korea

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