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

To allow wheelchair (electronic or manual) usersto practice driving in different safe, repeatable and controlledscenarios, the use of simulator as a training tool is consideredhere. In this context, the capabilities of providing high fidelitymotions for users of the simulator is highlighted as one of themost important aspects for the effectiveness of the tool. For thispurpose, the motion cueing algorithm (MCA) is studied in ourwork to regenerate wheelchair motion cues by transformingmotions of the real or simulated wheelchair into the simulatormotion. The studied algorithm is developed based on ModelPredictive Control (MPC) approach to efficiently optimize themotions of the platform. The overall problem is formulatedusing mixed-integer quadratic programming (MIQP) whichinvolves not only the vestibular model, strict constraints of theplatform but also the perception threshold in the optimizationcost function. In the end, the performance assessment of thesystem using different control techniques is analyzed, showingthe effectiveness of the proposed approach in the simulationenvironment.