Human perception-based washout filtering using genetic algorithm

Asadi, Houshyar, Mohamed, Shady, Nelson, Kyle, Nahavandi, Saeid and Zadeh, Delpak Rahim 2015, Human perception-based washout filtering using genetic algorithm, in 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II, Springer, New York, N.Y., pp. 401-411, doi: 10.1007/978-3-319-26535-3_46.

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Title Human perception-based washout filtering using genetic algorithm
Author(s) Asadi, HoushyarORCID iD for Asadi, Houshyar
Mohamed, ShadyORCID iD for Mohamed, Shady
Nelson, KyleORCID iD for Nelson, Kyle
Nahavandi, SaeidORCID iD for Nahavandi, Saeid
Zadeh, Delpak Rahim
Conference name Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)
Conference location Istanbul, Turkey
Conference dates 9-12 Nov. 2015
Title of proceedings 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II
Publication date 2015
Start page 401
End page 411
Total pages 11
Publisher Springer
Place of publication New York, N.Y.
Keyword(s) Science & Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Computer Science
Washout filter
Motion cueing algorithm (MCA)
Genetic algorithm (GA)
Human sensation
Summary The Motion Cueing Algorithm (MCA) transforms longitudinal and rotational motions into simulator movement, aiming to regenerate high fidelity motion within the simulators physical limitations. Classical washout filters are widely used in commercial simulators because of their relative simplicity and reasonable performance. The main drawback of classical washout filters is the inappropriate empirical parameter tuning method that is based on trial-and-error, and is effected by programmers’ experience. This is the most important obstacle to exploiting the platform efficiently. Consequently, the conservative motion produces false cue motions. Lack of consideration for human perception error is another deficiency of classical washout filters and also there is difficulty in understanding the effect of classical washout filter parameters on generated motion cues. The aim of this study is to present an effortless optimization method for adjusting the classical MCA parameters, based on the Genetic Algorithm (GA) for a vehicle simulator in order to minimize human sensation error between the real and simulator driver while exploiting the platform within its physical limitations. The vestibular sensation error between the real and simulator driver as well as motion limitations have been taken into account during optimization. The proposed optimized MCA based on GA is implemented in MATLAB/Simulink. The results show the superiority of the proposed MCA as it improved the human sensation, maximized reference signal shape following and exploited the platform more efficiently within the motion constraints.
ISBN 9783319265346
ISSN 0302-9743
Language eng
DOI 10.1007/978-3-319-26535-3_46
Field of Research 090602 Control Systems, Robotics and Automation
08 Information And Computing Sciences
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, Springer
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