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International Journal of Automation and Computing 2018, Vol. 15 Issue (2) :207-217    DOI: 10.1007/s11633-017-1065-z
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Multi-sensor Data Fusion for Wheelchair Position Estimation with Unscented Kalman Filter
Derradji Nada1, Mounir Bousbia-Salah1, Maamar Bettayeb2
1 LASA laboratory, Department of Electronics, Faculty of Engineering, Badji Mokhtar Annaba University, BP 12, Annaba 23000, Algeria;
2 Department of Electrical and Computer Engineering, College of Engineering, University of Sharjah, United Arab Emirates
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Abstract This paper investigates the problem of estimation of the wheelchair position in indoor environments with noisy measurements. The measuring system is based on two odometers placed on the axis of the wheels combined with a magnetic compass to determine the position and orientation. Determination of displacements is implemented by an accelerometer. Data coming from sensors are combined and used as inputs to unscented Kalman filter (UKF). Two data fusion architectures:measurement fusion (MF) and state vector fusion (SVF) are proposed to merge the available measurements. Comparative studies of these two architectures show that the MF architecture provides states estimation with relatively less uncertainty compared to SVF. However, odometers measurements determine the position with relatively high uncertainty followed by the accelerometer measurements. Therefore, fusion in the navigation system is needed. The obtained simulation results show the effectiveness of proposed architectures.
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KeywordsData fusion   unscented Kalman filter (UKF)   measurement fusion (MF)   navigation   state vector fusion (SVF)   wheelchair     
Received: 2015-07-24; Revised: 2016-05-11; published: 2017-03-20
Corresponding Authors: Mounir Bousbia-Salah     Email: bousbia.salah@univ-annaba.org
About author: Derradji Nada received the B. Sc. and M. Sc. degrees in electrical engineering from University of Bordj Bou Arreridj, Algeria in 2009 and 2011, respectively. E-mail:derradji.nada@univ-annaba.org;Mounir Bousbia-Salah received the B. Eng. degree in electronics from Annaba university. E-mail:bousbia.salah@univ-annaba.org;Maamar Bettayeb received the B. Sc., M. Sc., and Ph. D. degrees in electrical engineering from University of Southern California, USA in 1976, 1978 and 1981, respectively.E-mail:maamar@sharjah.ac.ae
Cite this article:   
Derradji Nada, Mounir Bousbia-Salah, Maamar Bettayeb. Multi-sensor Data Fusion for Wheelchair Position Estimation with Unscented Kalman Filter[J]. International Journal of Automation and Computing , vol. 15, no. 2, pp. 207-217, 2018.
http://www.ijac.net/EN/10.1007/s11633-017-1065-z      或     http://www.ijac.net/EN/Y2018/V15/I2/207
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