ハードウェア制約下のヒューマノイドロボットのための重心状態推定と制御
Centroidal State Estimation and Control for Hardware-constrained Humanoid Robots
力覚・接触センサや自由度が限られたヒューマノイドでも、5質量モデルで重心状態と圧力中心を推定し、フィードフォワード・フィードバック制御と反応的歩行でバランスを維持する手法を提案し、RoboCup 2023で実機検証した。
著者: Grzegorz Ficht, Sven Behnke
分類: cs.RO
原文アブストラクト
We introduce novel methods for state estimation, feedforward and feedback control, which specifically target humanoid robots with hardware limitations. Our method combines a five-mass model with approximate dynamics of each mass. It enables acquiring an accurate assessment of the centroidal state and Center of Pressure, even when direct forms of force or contact sensing are unavailable. Upon this, we develop a feedforward scheme that operates on the centroidal state, accounting for insufficient joint tracking capabilities. Finally, we implement feedback mechanisms, which compensate for the lack in Degrees of Freedom that our NimbRo-OP2X robot has. The whole approach allows for reactive stepping to maintain balance despite these limitations, which was verified on hardware during RoboCup 2023, in Bordeaux, France.
