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State estimation based on Kalman filtering techniques in navigation

Levente Tamás, Gh. Lazea, R. Robotin, C. Marcu, S. Herle, Zoltan Szekely

Year
2008
Citations
16

Abstract

This paper tackles the problem of the position measurement and estimation techniques in the robot navigation field based on Kalman filters. It presents the problem of the position estimation based on odometric, infrared and ultrasonic measurements. Further on deals with the theoretical and practical aspects of the state estimation based on Kalman filtering techniques. From the wide range of derivatives of the Kalman filtering technique there are detailed the Extended Kalman filter and the one based on Unscented Transformation. In the second part of the paper is concluded with the results of the comparison between the different filtering algorithms and the further perspectives regarding this subject.

Keywords

Kalman filterFast Kalman filterExtended Kalman filterComputer scienceInvariant extended Kalman filterPosition (finance)Alpha beta filterComputer visionTransformation (genetics)Artificial intelligence

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