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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 16 | Page No.: 2901-2906
DOI: 10.3923/jas.2008.2901.2906
 
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Design of Augmented Extended and Unscented Kalman Filters for Differential-Drive Mobile Robots

Iraj Hassanzadeh and Mehdi Abedinpour Fallah

Abstract:
In this study, we present the local reconstruction of differential-drive mobile robots position and orientation with an accurate odometry calibration. Starting from the encoders readings and assuming an absolute measurement available, Augmented Extended and Unscented Kalman Filters (AEUKF) are proposed to localize the vehicle while estimating a proper set of odometric parameters. In order to compare their estimation performances explicitly, both observers are designed for the same mobile robot model and run with the equal covariance matrices under the identical initial conditions. In the simulation results, it is shown that Augmented Unscented Kalman Filter (AUKF) outperforms the Augmented Extended Kalman Filter (AEKF).
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How to cite this article:

Iraj Hassanzadeh and Mehdi Abedinpour Fallah, 2008. Design of Augmented Extended and Unscented Kalman Filters for Differential-Drive Mobile Robots. Journal of Applied Sciences, 8: 2901-2906.

DOI: 10.3923/jas.2008.2901.2906

URL: https://scialert.net/abstract/?doi=jas.2008.2901.2906

COMMENTS
11 May, 2009
bassel:
hello,
i am student from syria ,i want to use your programe of EKF so if you please ,
can you send me the Matlab file for me ,please

thanks
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