A particle swarm optimization-based washout filter for improving simulator motion fidelity Asadi, Houshyar, Mohammadi, Arash, Mohamed, Shady, Lim, Chee Peng, Khatami, Amin, Khosravi, Abbas and Nahavandi, Saeid 2017, A particle swarm optimization-based washout filter for improving simulator motion fidelity, in SMC 2016 : Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, IEEE, Piscataway, N.J., pp. 1963-1968, doi: 10.1109/SMC.2016.7844527. Attached Files Name Description MIMEType Size Downloads Title A particle swarm optimization-based washout filter for improving simulator motion fidelity Author(s) Asadi, Houshyar orcid.org/0000-0002-3620-8693 Mohammadi, Arash orcid.org/0000-0001-7634-8212 Mohamed, Shady orcid.org/0000-0002-8851-1635 Lim, Chee Peng orcid.org/0000-0003-4191-9083 Khatami, Amin Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Systems, Man and Cybernetics. IEEE International Conference (2016 : Budapest, Hungary) Conference location Budapest, Hungary Conference dates 9-12 Oct. 2016 Title of proceedings SMC 2016 : Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics Editor(s) [Unknown] Publication date 2017 Conference series Systems, Man and Cybernetics IEEE International Conference Start page 1963 End page 1968 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) particle swarm optimization washout filter motion cueing algorithm human sensation Summary The washout filter for a driving simulator is able to regenerate high fidelity vehicle translational and rotational motions within the simulator's physical limitations and return the simulator platform back to its initial position. The classical washout filter provides a popular solution that has been broadly utilized in different commercial simulators due to its simplicity, short processing time, and reasonable performance. One limitation of the classical washout filter is its sub-optimal parameter tuning process, which is based on the trial-and-error method. This leads to an inefficient workspace usage and, consequently, generation of false motion cues that lead to simulator sickness. Ignorance of a human sensation model in its design is another drawback of classical washout filters. The purpose of this study is to use Particle Swarm Optimization (PSO) to design and tune the washout filter parameters, in order to increase motion fidelity, decrease the human sensation error, and improve efficiency of the workspace usage. The proposed PSO-based washout filter is designed and implemented using the MATLAB/Simulink software package. The results indicate the effectiveness of the PSO-based washout filter in reducing the human sensation error, increasing the capability of reference shape tracking, and improving efficiency of the workspace usage. ISBN 9781509018970 Language eng DOI 10.1109/SMC.2016.7844527 Field of Research 099999 Engineering not elsewhere classified Socio Economic Objective 970110 Expanding Knowledge in Technology HERDC Research category E1 Full written paper - refereed Copyright notice ©2016, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30093504 Document type: Conference Paper Collection: Institute for Frontier Materials Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 06 Apr 2017, 11:25:20 EST Fri, 07 Apr 2017, 05:03:15 EST Thu, 11 May 2017, 06:05:39 EST Fri, 26 May 2017, 13:35:26 EST Fri, 26 May 2017, 13:40:31 EST Fri, 26 May 2017, 13:41:12 EST Sat, 08 Jul 2017, 02:30:55 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 193 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Thu, 06 Apr 2017, 11:25:20 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.