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.
from cs updates on arXiv.org https://ift.tt/2KxGoz8
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