Turkish Journal of Electrical Engineering and Computer Sciences




In this paper, a new approach is developed, avoiding the correspondence problem caused by the difference in embodiment between imitator and demonstrator in imitation learning. In our work, the imitator is a fluidic system of dynamics totally different than the imitatee, which is a human performing hand gestures. The fluidic system is composed of fluid particles, which are used for the discretization of the problem domain. In this work, we demonstrate the fluidics formation control so as to imitate by observation basic hand preshaping features. Our fluidic formation control is based on setting suitable parameters of Smoothed Particle Hydrodynamics (SPH), which is a particle based Lagrangian method, according to imitation learning. The fluid parameters adjusted by the fluidics imitation controller are body force (f), density and velocity of particles (V) so as to lead formations of fluidic swarms to human hand preshapes.

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