Optimizing an Optimization-Based MCA using Perceived Motion Incongruence Models

Cleij, Diane; Pool, D.M.; Mulder, Max; Bulthoff, Heinrich H.

Optimizing an Optimization-Based MCA using Perceived Motion Incongruence Models

Conference paper (2020)

Authors

Diane Cleij Max Planck Institute for Biological Cybernetics,

D.M. Pool

Max Mulder

Heinrich H. Bulthoff Max Planck Institute for Biological Cybernetics

Model predictive control Motion cueing algorithms Motion incongruence models Continuous ratings

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Published Date

2020

Language

English

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Abstract

In this paper the potential of Motion Incongruence Rating (MIR) models for the optimization of Motion Cueing Algorithms (MCAs) is investigated. In a human-in-the-loop simulator experiment, two optimization-based MCAs are compared for a roundabout scenario simulated on a medium-stroke hexapod simulator. The first MCA uses standard cueing error weights from reference literature in its cost function, while for the second case these weights were based on a MIR model fitted to previous experiment data. Results show that such models provide a promising cueing error weight estimation method for optimization-based MCAs, but also highlight the limitations of these models due to, for example, their dependency on the richness of the datasets to which they are fitted.

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