Global estimation of robot's attitude via quaternion and data fusion

Generally, the attitude estimation and the measurement of the angular velocity are a requirement for the attitude control. As a result, the computational cost and the complexity of the control loop are relatively high. In the present paper, a technique for attitude stabilization is proposed; the technique proposed is designed with attitude estimation and the prediction of the movement. With this approach, only the measurements of at least two non-collinear directional sensors are needed. Since the control laws are highly simple and a model-based observer for angular velocity reconstruction is not needed, the proposed new strategy is very suitable for embedded implementations. The global convergence of the estimation and prediction techniques is proved. Simulations with some robustness tests are performed.