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Model predictive motion cueing for a helicopter hover task on an 8-dof serial robot simulator

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dc.contributor.author Drop, F.M.
dc.contributor.author Olivari, M.
dc.contributor.author Geluardi, S.
dc.contributor.author Katliar, M.
dc.contributor.author Bülthoff, H.H.
dc.date.accessioned 2021-03-04T15:52:54Z
dc.date.available 2021-03-04T15:52:54Z
dc.date.issued 2018
dc.identifier.other 125 - Model Predictive Motion Cueing for a Helicopter Hover Task on an 8....pdf
dc.identifier.uri http://hdl.handle.net/20.500.11881/4020
dc.description.abstract Motion cueing for helicopter hover is difficult: small simulators require considerable attenuation, rendering motion cues not useful for stabilization, and large simulators are typically not cost effective. Industrial serial robot-based simulators provide large motion capabilities at a moderate cost, but have two distinct disadvantages. First, they are highly dimensional systems with a non-convex motion space, such that efficient use of the entire space is not trivial. Second, they are typically non-stiff structures with a large mass at the end effector, resulting in oscillatory dynamical properties. We recently developed a novel Model Predictive Motion Cueing Algorithm (MPMCA) that resolves both problems effectively for pre-recorded inertial reference signals. The MPMCA requires an accurate prediction of the future course of the reference inertial signals, which is trivial for pre-recorded maneuvers, but not for real-time human-in-the-loop simulations. In this paper, we present a model-based prediction method, which predicts pilot control inputs and the subsequent helicopter inertial signals during a helicopter hover simulation in real-time. The method is tested in a human-in-the-loop experiment and compared with the Classic Washout Algorithm. The results demonstrate that the MPMCA is a promising new approach to motion cueing.
dc.language.iso en
dc.title Model predictive motion cueing for a helicopter hover task on an 8-dof serial robot simulator


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