低次元モデルによるマルチドメイン歩行
Multi-Domain Walking with Reduced-Order Models of Locomotion
人間の多様な歩行をハイブリッド力学系として捉え、マルチドメイン線形倒立振子モデルを構築し、二足歩行ロボットCassieで速度追従や外乱回復を実現した。
著者: Min Dai, Jaemin Lee, Aaron D. Ames
分類: cs.RO
原文アブストラクト
Drawing inspiration from human multi-domain walking, this work presents a novel reduced-order model based framework for realizing multi-domain robotic walking. At the core of our approach is the viewpoint that human walking can be represented by a hybrid dynamical system, with continuous phases that are fully-actuated, under-actuated, and over-actuated and discrete changes in actuation type occurring with changes in contact. Leveraging this perspective, we synthesize a multi-domain linear inverted pendulum (MLIP) model of locomotion. Utilizing the step-to-step dynamics of the MLIP model, we successfully demonstrate multi-domain walking behaviors on the bipedal robot Cassie -- a high degree of freedom 3D bipedal robot. Thus, we show the ability to bridge the gap between multi-domain reduced order models and full-order multi-contact locomotion. Additionally, our results showcase the ability of the proposed method to achieve versatile speed-tracking performance and robust push recovery behaviors.
