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.