最大CPI集合に基づくスイッチングフィードバック制御によるヒューマノイドロボットの安定化

概要

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Humanoid robots should be able to stand and walk in the presence of external disturbances. Humans usually switch the control strategies depending on disturbances: stabilization in the upright position, and falling avoidance using stepping motion. In order to achieve robustness to unknown disturbances, humanoid robots require switching the control strategies. For this purpose, it is important to explicitly consider the physical constraint in the control law. In this paper, we apply the maximal CPI set framework to the control based on the COG-ZMP inverted pendulum model. Based on the maximal CPI set, we can determine whether the constraint is broken or not. Furthermore, we improve the robustness to external disturbances by applying a switching feedback control based on the maximal CPI sets. We also present a real-time updating method of the maximal CPI set when the contact region changes. Using this updating method, a falling avoidance control method is proposed as an application. Detection of the stepping necessity based on the maximal CPI set enables the robots to switch the control strategies from the upright position stabilization to the stepping motion for falling avoidance. The validity of the proposed method is verified with simulations and experiments.