Generation Human Body Motion by the Centralized Networks

The main goal of the thesis is to describe and study reduced models for efficient simulations of human body motions (HBM). To this end, we propose new coupled oscillator models, which are networks of dynamically coupled elements. These networks consist of a few of centers and many satellites. The centers evolve in time as periodical oscillators with different frequencies. The satellite states are defined via center states by a radial basis function (RBF) networks. To simulate different motions we adjust the parameter of the RBF networks and frequencies of centers. Moreover, our network includes a switching module that allows to turn from a motion to another one, say, from jumping to walking. It is shown that this model is capable to simulate complicated motions consisting of many different elements dynamical primitives (walking, running, jumping etc.).