Switching multiple LQG controllers based on bellman´s optimality principle: Using full-state feedback to control a humanoid robot

In this study, we propose novel modular architecture to control a robot with many degrees of freedom, such as a humanoid robot. High-degree-of-freedom (DOF) robots tend to have highly nonlinear dynamics. In general, deriving a nonlinear controller for high-dimensional systems is intractable. In our approach, we adopt multiple Linear Quadratic Gaussian (LQG) controllers to cope with nonlinear dynamics. Switching criteria for the modular architecture is provided by Bellman´s optimality. The proposed method is applied to a simulated 10-DOF biped model and a 51-DOF humanoid robot called CB-i.