Informed priority control for humanoids

Abstract

We describe and demonstrate informed priority control, a control architecture for humanoid robots based on the coordination of multiple sub-policies. While many humanoid robot controllers are designed to maintain orthogonality between sub-policies, informed priority control facilitates directional dependencies between sub-policies. This facilitation is achieved by using a cascade control architecture augmented with models of each partial cascade. We describe the method we use to automatically generate these models in response to changes in sub-policy configuration. Additionally, we demonstrate an implementation of the informed priority framework that can robustly balance a simulated humanoid robot on a bongo-board. © 2011 IEEE.