FORGE: 俊敏なヒューマノイド歩行のための実行可能なオンライン低次元参照生成と全身制御
FORGE: Feasible Online Reduced-Order Reference Generation and Whole-Body Execution for Agile Humanoid Locomotion
低次元モデルで参照軌道をオンライン生成し、それを全身追従制御の学習に用いる2段階学習フレームワークを提案。Unitree G1で高速移動や片脚ホッピングなど多様な歩行を単一ポリシーで実現した。
著者: Adrian B. Ghansah, Yujin An, Jeeseop Kim, Soon-Jo Chung
分類: cs.RO, cs.LG
原文アブストラクト
This paper presents a two-stage learning framework for versatile and agile humanoid locomotion that couples online reduced-order model (ROM) reference generation with whole-body tracking control. In the first stage, we train a command-conditioned whole-body reference generator using single rigid body dynamics combined with full humanoid kinematics. In the second stage, the frozen ROM policy is rolled out online to generate references for training a whole-body tracking policy on the full-order dynamics model. Learning a kino-dynamically consistent reference generator in the simplified ROM space enables us to generate references over a broad command space and over multiple locomotion strategies using a single unified framework. We demonstrate the approach on a Unitree G1 humanoid robot, achieving longitudinal velocities from -2.0 m/s to 2.8 m/s, lateral velocities up to +-1.0 m/s, angular velocities up to +-3.0 rad/s, one-legged hopping, and continuous transitions across the commands, all using one unified reference policy and one whole-body tracking policy.