Authors:
Hatem Elloumi
;
Marc Bordier
and
Nadia Mäızi
Affiliation:
Centre de Mathématiques Appliquées, École des Mines de Paris, France
Keyword(s):
Driving simulation, optimal motion cueing, Gough-Stewart platform, motion perception.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Modeling, Simulation and Architectures
;
Robot Design, Development and Control
;
Robotics and Automation
;
Vehicle Control Applications
Abstract:
Within the framework of driving simulation, control is a key issue to providing the driver realistic motion cues. Visual stimulus (virtual reality scene) and inertial stimulus (platform motion) induce a self-motion illusion. The challenge is to provide the driver with the sensations he would feel in real car maneuvering. This is an original control problem. Indeed, the first goal is not classical path tracking but fooling the driver awareness. Constrained workspace is the second issue classically addressed by motion cueing algorithms. The purpose of this paper is to extend the works of Telban and Cardullo on the optimal motion cueing algorithm. A nonlinear dynamical model of the robot is brought in. The actuator forces are directly included in the optimal control scheme. Consequently a better (global) optimization and an advanced parametrization of the control are achieved.