  Locomotion of legged machines faces the problems of model complexity and
computational costs. Algorithms based on complex models and/or reinforcement
learning exist to solve the walking control task. In this project, we aim to
develop a bipedal walking control system based on a simple model the Linear
Inverted Pendulum model. In order to simplify the complex process of
controlling legged locomotion, we make use of the technique of splitting the
control into three parts as height control, forward velocity control and
balance control. The forward velocity of the body has a linear relationship
with the foot placement, therefore we use a linear function to realise foot
placement. Our control system achieves stable walking gait in a simulated
environment, where our bipedal robot walks more than 200 steps with a cyclic
pattern in a stable, dynamic and almost natural manner. The experimental data
are presented and analysed.
