Optimal Filtering for Humanoid Robot State Estimators

In controlling a humanoid robot, state estimators are used to estimate condition of motion and orientation of the body part which will be feedbacked to control systems to regulate level of the body along with controlling trajectory of center of gravity (C.G.) of the robot. In this research, an algorithm for state estimators is developed by applying the H2-norm optimal filtering technique to a linearized dynamic model of the body part of the robot.