Generating Motion by Optimizing The Rowat and Silverstone of Neural Oscillator for Defining Human Gait Patterns

Abstract

This study discusses the effect of the Rowat and Silverstone of Neural Oscillator for Defining Human Gait ‎Patterns ‎by using both the Genetic Algorithm and hybrid function. By omitting pulse generators in the Rowat and Silverstone of Neural Oscillator, because of that it changes to a new type of Central Patterns Generator. By optimizing a new type and compare with the real data that we get from Tema Motion software. This paper will show that it is possible to produce rhythmic patterns like the rhythmic patterns derived from real data without any sensor feedback. This study will also be concerned with the most effective parameters of the Rowat and Silverstone Neural Oscillator