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Human perception-based washout filtering using genetic algorithm
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posted on 2015-01-01, 00:00 authored by Houshyar AsadiHoushyar Asadi, Shady MohamedShady Mohamed, Kyle Nelson, Saeid Nahavandi, D R ZadehThe 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.
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Volume
9490Pagination
401 - 411Publisher DOI
ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319265346Publication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, SpringerUsage metrics
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