A Mixed-Integer Model Predictive Control Approach to Motion Cueing in Immersive Wheelchair Simulator

To allow wheelchair (electronic or manual) users to practice driving in different safe, repeatable and controlled scenarios, the use of simulator as a training tool is considered here. In this context, the capabilities of providing high fidelity motions for users of the simulator is highlighted as one of the most important aspects for the effectiveness of the tool. For this purpose, the motion cueing algorithm (MCA) is studied in our work to regenerate wheelchair motion cues by transforming motions of the real or simulated wheelchair into the simulator motion. The studied algorithm is developed based on Model Predictive Control (MPC) approach to efficiently optimize the motions of the platform. The overall problem is formulated using mixed-integer quadratic programming (MIQP) which involves not only the vestibular model, strict constraints of the platform but also the perception threshold in the optimization cost function. In the end, the performance assessment of the system using different control techniques is analyzed, showing the effectiveness of the proposed approach in the simulation environment.