Adaptive Washout Algorithm for 360° Rotational Stewart Platforms in VR-Integrated Driving Simulators

Conventional Stewart platform-based motion simulators are constrained by a limited workspace, particularly in the yaw degree of freedom. Washout algorithms are typically employed to condense vehicle motion cues into these physical constraints, replicating sustained inertial sensations through coordinated filtering and transformation. The advent of Virtual Reality (VR) in driving simulation, coupled with the development of novel Stewart platforms capable of unlimited rotation about the yaw axis, exposes a critical flaw in classical washout methods. Their inherent restriction of yaw channel motion creates a perceptional disconnect from the unbounded visual steering cues in VR, frequently inducing simulator sickness. This paper introduces a refined washout algorithm, specifically designed for deep integration between 360° rotatable platforms and VR content. The core innovation lies in the decoupling of vehicular angular motion: high-frequency, transient components are allocated to the physical platform, while low-frequency, sustained components are rendered through the VR visual display. A comprehensive mathematical framework of the proposed algorithm is derived. Validation is conducted via a co-simulation environment, integrating a high-fidelity vehicle dynamics model with a VR training scenario. Results demonstrate a significant enhancement in the congruity between motion cues and visual feedback, effectively mitigating simulator-induced discomfort.