Original scientific paper

https://doi.org/10.17559/TV-20140531190647

Locating a two-wheeled robot using extended Kalman filter

Javad Zolghadr ; School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Yuanli Cai ; School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Abstract

The Kalman filter is a very general method of filtering which can solve problems such as optimal estimation, prediction, noise filtering, and optimal control. A problem with detection of correct path of moving objects is the received noisy data. Therefore, it is possible that the information is incorrectly detected. There are Different methods to extract the correct data from the received information. This paper aims to detect the path of a two-wheeled robot using extended Kalman filter. For this purpose, triangular, circular, elliptical, and Sinusoidal paths were used to explore various scenarios. The results showed that the Kalman filter optimally detects the correct path with less than 3 % error rate. These results also show that error rate related to detect circular and triangular paths has the highest and lowest value, respectively, using the extended Kalman filter; in addition, the results showed that the error rate strongly depends on path changes.

Keywords

path detection; the extended Kalman filter tracking; two-wheeled robot

Hrčak ID:

149378

URI

https://hrcak.srce.hr/149378

Publication date:

14.12.2015.

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