Optimizing an Optimization-Based MCA using Perceived Motion Incongruence Models

Conference paper (2020)

Authors

D. Cleij Max Planck Institute for Biological Cybernetics,
Heinrich H. Bülthoff Max Planck Institute for Biological Cybernetics
Copyright: © 2020 D. Cleij, D.M. Pool, Max Mulder, Heinrich H. Bülthoff
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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.