Abstract
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.
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© 2012 Springer-Verlag Berlin Heidelberg
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Ha, X.V., Ha, C., Lee, J. (2012). Trajectory Estimation of a Tracked Mobile Robot Using the Sigma-Point Kalman Filter with an IMU and Optical Encoder. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_54
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DOI: https://doi.org/10.1007/978-3-642-31588-6_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31587-9
Online ISBN: 978-3-642-31588-6
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