Development of a G-Seat Force Cueing Algorithm for Motion Simulation

Abstract

Motion simulators aim to replicate the sensation of movement to enhance realism in flight training and research applications. To achieve this goal, motion cues, including but not limited to vestibular, pressure, and visual, are typically employed. By combining the motion of robotic platforms such as hexapods and robotic arms, combined with visual and sensory feedback, motion simulators create highly immersive experiences that mimic real-world vehicle dynamics. G-seats, equipped with pressure-based actuators to simulate acceleration and maneuvering forces, play a crucial role in these type of systems, especially when large-scale motion platforms are unavailable or have limited mobility. Due to workspace constraints, motion simulators are unable to reproduce low-frequency sustained accelerations. To overcome this limitation, prototype flap actuators integrated into the seat have been designed to provide localized pressure cues, aiming to enhance the fidelity of perceived pressure. This thesis focuses on the design of an optimal washout algorithm for motion cueing (also known as force cueing), tailored for the actuators to be integrated into the Robotic Motion Simulator (RMS) system at the German Aerospace Center (DLR). Specifically, a somatosensory pressure model is integrated into an LRQ-based control strategy to generate the optimal signal for the actuators, aiming to accurately replicate the pressure a pilot would experience in a real vehicle. The effectiveness of the algorithm was evaluated through software simulations and compared with a classical washout algorithm highlighting the improvement that can be obtained.