Control strategy switching for humanoid robots based on maximal output admissible set

• A novel framework for control strategy switching based on the maximal output admissible set (MOA) set is proposed.
• The formulation and computation procedure for the MOA set are presented for trajectory tracking control.
• The MOA set was applied to the falling prevention control. By switching between the regulator and trajectory tracking controller based on the MOA set, the robot can avoid falling with the COP constraint satisfied.
• An experimental computation method for the MOA set via identification of the macroscopic feedback gain is proposed. The validity of this framework was verified by the results of experiments.

Human-like bipedal walking is a goal of humanoid robotics. It is especially important to provide a robust falling prevention capability by imitating the human ability to switch between control strategies in response to disturbances, e.g., standing balancing and stepping motion. However, the motion control of a humanoid robot is challenging because the contact forces are constrained. This paper proposes a novel framework for control strategy switching based on the maximal output admissible (MOA) set, which is a set of initial states that satisfy the constraints. This makes it possible to determine whether the robot might fall down due to a constraint violation. The MOA set is extended to a trajectory tracking controller with a time-variant reference and constraint. In this extension, the motion of the vertical center of gravity is also considered, which has often been neglected in previous studies. Utilizing the MOA set, an example is shown of the falling prevention control by switching the standing balance control and trajectory tracking control to a stepping and hopping motion. Moreover, a method is presented for applying the MOA set framework to a position-controlled humanoid robot. The validity of the MOA set framework is verified based on simulations and experimental results.