  In this paper, a simple Neural controller has been used to achieve stable
walking in a NAO biped robot, with 22 degrees of freedom that implemented in a
virtual physics-based simulation environment of Robocup soccer simulation
environment. The algorithm uses a Matsuoka base neural oscillator to generate
control signal for the biped robot. To find the best angular trajectory and
optimize network parameters, a new population-based search algorithm, called
the Harmony Search (HS) algorithm, has been used. The algorithm conceptualized
a group of musicians together trying to search for better state of harmony.
Simulation results demonstrate that the modification of the step period and the
walking motion due to the sensory feedback signals improves the stability of
the walking motion.
