Adaptive washout algorithm based fuzzy tuning for improving human perception Asadi,H, Mohammadi,A, Mohamed,S, Zadeh,DR and Nahavandi,S 2014, Adaptive washout algorithm based fuzzy tuning for improving human perception. In Loo,CK, Yap,KS, Wong,KW, Teoh,A and Huang,K (ed), Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part III, Springer, Berlin, Germany, pp.483-492, doi: 10.1007/978-3-319-12643-2_59. Attached Files Name Description MIMEType Size Downloads Title Adaptive washout algorithm based fuzzy tuning for improving human perception Author(s) Asadi,H orcid.org/0000-0002-3620-8693 Mohammadi,A Mohamed,S orcid.org/0000-0002-8851-1635 Zadeh,DR Nahavandi,S orcid.org/0000-0002-0360-5270 Title of book Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part III Editor(s) Loo,CK Yap,KS Wong,KW Teoh,A Huang,K Publication date 2014 Series Lecture notes in computer science ; v.8836 Chapter number 59 Total chapters 83 Start page 483 End page 492 Total pages 10 Publisher Springer Place of Publication Berlin, Germany Keyword(s) Fuzzy Logic Human perception Motion Cueing Algorithm Washout filter Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Information Systems Computer Science, Theory & Methods Computer Science Summary The aim of this paper is to provide a washout filter that can accurately produce vehicle motions in the simulator platform at high fidelity, within the simulators physical limitations. This is to present the driver with a realistic virtual driving experience to minimize the human sensation error between the real driving and simulated driving situation. To successfully achieve this goal, an adaptive washout filter based on fuzzy logic online tuning is proposed to overcome the shortcomings of fixed parameters, lack of human perception and conservative motion features in the classical washout filters. The cutoff frequencies of highpass, low-pass filters are tuned according to the displacement information of platform, workspace limitation and human sensation in real time based on fuzzy logic system. The fuzzy based scaling method is proposed to let the platform uses the workspace whenever is far from its margins. The proposed motion cueing algorithm is implemented in MATLAB/Simulink software packages and provided results show the capability of this method due to its better performance, improved human sensation and exploiting the platform more efficiently without reaching the motion limitation. ISBN 9783319126425 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-12643-2_59 Field of Research 090602 Control Systems, Robotics and Automation Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category B1 Book chapter ERA Research output type B Book chapter Copyright notice ©2014, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30070717 Document type: Book Chapter Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research 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 Mon, 16 Mar 2015, 14:40:08 EST Tue, 17 Mar 2015, 04:04:03 EST Tue, 31 Mar 2015, 15:56:57 EST Thu, 16 Apr 2015, 06:06:42 EST Tue, 21 Apr 2015, 10:57:11 EST Tue, 21 Apr 2015, 11:00:28 EST Tue, 21 Apr 2015, 14:27:42 EST Tue, 19 May 2015, 14:56:19 EST Tue, 19 May 2015, 14:58:08 EST Fri, 22 May 2015, 12:37:06 EST Mon, 25 May 2015, 08:14:06 EST Fri, 12 Jun 2015, 13:38:08 EST Mon, 23 Nov 2015, 09:41:37 EST Tue, 08 Dec 2015, 14:43:27 EST Fri, 25 Nov 2016, 15:15:20 EST Thu, 01 Jun 2017, 09:26:46 EST Filtered Full Citation counts:   Cited 17 times in TR Web of Science Cited 28 times in Scopus Search Google Scholar Access Statistics: 699 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Tue, 31 Mar 2015, 15:56:57 EST

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