ステップ調整を伴うヒューマノイド歩行のための離散時間モデル予測制御
Discrete time model predictive control for humanoid walking with step adjustment
低次元LIPMで足配置とCoM軌道をオンライン調整するMPCと全身トルク制御を組み合わせ、押し外乱に耐える安定歩行をシミュレーションで実現した。
著者: Vishnu Joshi, Suraj Kumar, Nithin V, Shishir Kolathaya
分類: cs.RO
原文アブストラクト
This paper presents a Discrete-Time Model Predictive Controller (MPC) for humanoid walking with online footstep adjustment. The proposed controller utilizes a hierarchical control approach. The high-level controller uses a low-dimensional Linear Inverted Pendulum Model (LIPM) to determine desired foot placement and Center of Mass (CoM) motion, to prevent falls while maintaining the desired velocity. A Task Space Controller (TSC) then tracks the desired motion obtained from the high-level controller, exploiting the whole-body dynamics of the humanoid. Our approach differs from existing MPC methods for walking pattern generation by not relying on a predefined foot-plan or a reference center of pressure (CoP) trajectory. The overall approach is tested in simulation on a torque-controlled Humanoid Robot. Results show that proposed control approach generates stable walking and prevents fall against push disturbances.
