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

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• 作者：Xuan Vinh Ha (20)
  Cheolkeun Ha (20)
  Jewon Lee (21)
  
• 关键词：Tracked mobile robots ; Inertial Measurement Unit (IMU) ; Sensor fusion ; Sigma ; Point Kalman Filter (SPKF)
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7389
• 期：1
• 页码：423-432
• 全文大小：525KB
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  8. Yi, J., Wang, H., Zhang, J., Song, D., Jayasuriya, S., Liu, J.: Kinematic Modeling and Analysis of Skid-Steered Mobile Robots With Ap-plications to Low-Cost Inertial-Measurement-Unit-Based Motion estimation. IEEE Transactions on Robotics聽25, 1087鈥?097 (2009) CrossRef
  
• 作者单位：Xuan Vinh Ha (20)
  Cheolkeun Ha (20)
  Jewon Lee (21)
  
  20. School of Mechanical Engineering, University of Ulsan, Republic of Korea
  21. Prigent Ltd., Republic of Korea
  

文摘

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.