全身ダイナミクスを用いた非線形モデル予測制御による平面二足歩行のオンライン歩容生成
Planar Bipedal Locomotion with Nonlinear Model Predictive Control: Online Gait Generation using Whole-Body Dynamics
二足ロボットの全身剛体ダイナミクスをオンラインの非線形モデル予測制御に組み込み、オフライン歩容との併用も可能にして多様な歩行を実現し、シミュレーションと実機で検証した。
著者: Manuel Y. Galliker, Noel Csomay-Shanklin, Ruben Grandia, Andrew J. Taylor, Farbod Farshidian, Marco Hutter, Aaron D. Ames
分類: cs.RO
原文アブストラクト
The ability to generate dynamic walking in real-time for bipedal robots with input constraints and underactuation has the potential to enable locomotion in dynamic, complex and unstructured environments. Yet, the high-dimensional nature of bipedal robots has limited the use of full-order rigid body dynamics to gaits which are synthesized offline and then tracked online. In this work we develop an online nonlinear model predictive control approach that leverages the full-order dynamics to realize diverse walking behaviors. Additionally, this approach can be coupled with gaits synthesized offline via a desired reference to enable a shorter prediction horizon and rapid online re-planning, bridging the gap between online reactive control and offline gait planning. We demonstrate the proposed method, both with and without an offline gait, on the planar robot AMBER-3M in simulation and on hardware.
