Abstract-This paper presents a driving simulation which aim is twofold: (i) investigate the possibility to reduce motion clearance in order to achieve compact and low cost driving simulators, and (ii) evaluate multimodal and immersive virtual reality motion restitution in platooning driving. The choice has been made for a driving simulator having at least two degrees of freedom. These consist of the longitudinal displacement and seat rotations. The simulator is also equipped with force feedback steering wheel for virtual drive assistance. These components are gathered on a serial kinematics type platform in order to facilitate control scheme, and avoid the architecture complexity. A comparative study was made to devise a motion cueing strategy, taking into account both psychophysical and technological constraints. Experimentations were carried out for several cases combinations of longitudinal displacement and seat rotations.
the paper deals with control of small driving simulator SIM² comparing the useless of adaptive and classic approaches. Driving simulators are considering as an interactive virtual reality tools, which take a considerable place in the human factors studies. The difficulty to reproduce in reality some drive situations mainly for risk and reproducibility reasons increases the interest of this tool. Nevertheless, the validation of the experiments carried out on driving simulator is closely related to embedding realism of the driver in the simulated world.In this article, we present the design of a low cost and small motion platform, which allow the restitution of 2 DOF movements. This overall system is considered as two independent systems linked mechanically. The first system consists in motorized rail for the longitudinal movement while the second system consists in motorized seat allowing either pitch movement of this one or just back seat inclination (this case will not be discussed in the rest of paper).
A common issue of the parallel robot is that has a large number of dynamic parameters, which requires a lot of processing time, whether in dynamic modeling, identification or control. The optimization and estimation of inertial parameters of a large DoF number of robotic system is crucial to tune the model-based control law in order to improve the robot accuracy. In this paper, we present an optimized number of dynamic parameters, called base inertial parameters. As a result, only 90 base inertial parameters affect the evr@ simulator instead of 210 standard one. Torque signals evaluation from experimental parallel platform and the developed analytical form show the effectiveness of the obtained results.
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