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Motion cueing algorithms are commonly used in vehicle simulators to control robotic motion platforms. These algorithms usually have a significant number of parameters that need to be tuned. This process has been traditionally performed in a pilot-in-the-loop subjective manner. The authors propose a simulation-based objective and automatic method using heuristic optimization. Several schemes are proposed, assessed and compared in this paper, showing that a genetic algorithm is the one that suits best this problem.

Heurísticas para el Ajuste de Algoritmos de Control de Plataformas Robóticas de Movimiento en Simuladores