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Towards a simulation-based tuning of motion cueing algorithms.

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Title: Towards a simulation-based tuning of motion cueing algorithms.
Authors: Casas, Sergio1 Sergio.Casas@uv.es, Coma, Inmaculada1, Portalés, Cristina1, Fernández, Marcos1
Source: Simulation Modelling Practice & Theory. Sep2016, Vol. 67, p137-154. 18p.
Subjects: Tuning (Machinery), Teleprompters, Algorithms, Robot motion, Virtual reality
Abstract: This paper deals with the problem of finding the best values for the parameters of Motion Cueing Algorithms (MCA). MCA are responsible for controlling the movements of robotic motion platforms used to generate the gravito-inertial cues of vehicle simulators. The values of their multiple parameters, or coefficients, are hard to establish and they dramatically change the behaviour of MCA. The problem has been traditionally addressed in a subjective, partially non-systematic, iterative, time-consuming way, by seeking pilot/driver feedback on the generated motion cues. The aim of this paper is to introduce a different approach to solve the problem of MCA tuning, by making use of a simulated motion platform; a series of (human-based) objective metrics relating to the performance of MCA are measured using this simulated device. This simulation-based approach allows for automatic tuning of the MCA, by using a genetic algorithm that is proposed to analyse the results obtained from multiple simulations of the MCA with different parameters. This algorithm is designed to efficiently optimize the simulated MCA parameter space. The proposed solution is assessed with the classical washout MCA, performing a series of tests to validate the correctness of this approach and the suitability of the proposed method to the solution of the MCA tuning problem. Results show that this approach can be an alternative to the traditional subjective tuning method in certain situations, mainly because it provides suitable values for the MCA parameters in a shorter time period, albeit subjective tuning is preferred when time to perform the MCA tuning is not an issue. [ABSTRACT FROM AUTHOR]
Copyright of Simulation Modelling Practice & Theory is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 117497435
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Towards a simulation-based tuning of motion cueing algorithms.
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  Data: <searchLink fieldCode="JN" term="%22Simulation+Modelling+Practice+%26+Theory%22">Simulation Modelling Practice & Theory</searchLink>. Sep2016, Vol. 67, p137-154. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Tuning+%28Machinery%29%22">Tuning (Machinery)</searchLink><br /><searchLink fieldCode="DE" term="%22Teleprompters%22">Teleprompters</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+motion%22">Robot motion</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+reality%22">Virtual reality</searchLink>
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  Label: Abstract
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  Data: This paper deals with the problem of finding the best values for the parameters of Motion Cueing Algorithms (MCA). MCA are responsible for controlling the movements of robotic motion platforms used to generate the gravito-inertial cues of vehicle simulators. The values of their multiple parameters, or coefficients, are hard to establish and they dramatically change the behaviour of MCA. The problem has been traditionally addressed in a subjective, partially non-systematic, iterative, time-consuming way, by seeking pilot/driver feedback on the generated motion cues. The aim of this paper is to introduce a different approach to solve the problem of MCA tuning, by making use of a simulated motion platform; a series of (human-based) objective metrics relating to the performance of MCA are measured using this simulated device. This simulation-based approach allows for automatic tuning of the MCA, by using a genetic algorithm that is proposed to analyse the results obtained from multiple simulations of the MCA with different parameters. This algorithm is designed to efficiently optimize the simulated MCA parameter space. The proposed solution is assessed with the classical washout MCA, performing a series of tests to validate the correctness of this approach and the suitability of the proposed method to the solution of the MCA tuning problem. Results show that this approach can be an alternative to the traditional subjective tuning method in certain situations, mainly because it provides suitable values for the MCA parameters in a shorter time period, albeit subjective tuning is preferred when time to perform the MCA tuning is not an issue. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Simulation Modelling Practice & Theory is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.simpat.2016.06.002
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 137
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      – SubjectFull: Tuning (Machinery)
        Type: general
      – SubjectFull: Teleprompters
        Type: general
      – SubjectFull: Algorithms
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      – SubjectFull: Robot motion
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      – SubjectFull: Virtual reality
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      – TitleFull: Towards a simulation-based tuning of motion cueing algorithms.
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            NameFull: Casas, Sergio
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            NameFull: Coma, Inmaculada
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            NameFull: Portalés, Cristina
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            – D: 01
              M: 09
              Text: Sep2016
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              Y: 2016
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