Research/ ORBITAL ROBOTICS
Modified Optimal Motion Cueing Algorithm with Haptic Feedback for Full Motion Simulation for a Reduced Gravity Environment
Julia Born, Andreas Seefried, Miguel Neves, Houshyar Asadi, Tobias Bellmann
HRI & TeleoperationOpenAlex topic: Teleoperation and Haptic Systems · Surface Mobility & TerramechanicsOpenAlex topic: Vehicle Dynamics and Control Systems
Motion simulators are used in the development and training of novel vehicle control concepts, including those intended for future lunar landings. To ensure the transferability of the results, the vehicle motions must be reproduced as realistically as possible using Motion Cueing Algorithm (MCAs). MCAs are responsible for transforming real vehicle motions into simulator motions, aiming to generate realistic sensations for the users. Since reduced gravity cannot be accurately simulated on Earth over an extended period, this presents a challenge for scenarios in low-gravity environments, requiring the definition of appropriate error-handling strategies. In this work, an optimal motion cueing algorithm is designed and developed to minimize the perception error between the simulator user and vehicle user by taking into account a human perception model that accounts for different gravitational forces. The algorithm attempts to correctly represent angular rates and linear accelerations while assuming an orientation error. To address this limitation, a force feedback stick is integrated into the motion cueing to represent the current vehicle orientation. The algorithm is tested and compared to a classical washout filter in a piloted simulator campaign in combination with the force feedback. The results indicate that the proposed algorithm is a valid approach with the potential for further optimization through modified parameterization. The force feedback stick improves situational awareness and enhances flight perception.