Control humanoid robot using intelligent optimization algorithms fusion with fourier series

Abstract

Robot walking on two feet is a complex motion. Researchers are trying to improve biped robots walking in case of walking speed. The analysis of biped walking patterns is used to obtain more detailed information in this field. Several researches have been done to achieve this purpose and the equation of walking trajectory is one of them. This article will introduce a new algorithm in which an evolutionary computing, based on learning automata along with a continual action on control signals of humanoid robot's motion, showing the success of the proposed method as the result to be used for optimizing the parameters of Truncated Fourier Series (TFS) after being compared with the results of Genetic Algorithm (GA) implementation. It is notable that the conditions of the experiment for these two algorithms are considered to be identical.