FastMimic：敏捷・多様・汎化可能な四足歩行のためのモデルベース動作模倣
FastMimic: Model-based Motion Imitation for Agile, Diverse and Generalizable Quadrupedal Locomotion
動物の歩容をセントロイダル動力学モデルとオンライン適応で模倣する統一的なモデルベース制御法を提案し、高価なシミュレーション学習や実機微調整なしで多様な運動を実現した。
著者: Tianyu Li, Jungdam Won, Sehoon Ha, Akshara Rai
分類: cs.RO
原文アブストラクト
Robots operating in human environments need various skills, like slow and fast walking, turning, side-stepping, and many more. However, building robot controllers that can exhibit such a large range of behaviors is a challenging problem that requires tedious investigation for every task. We present a unified model-based control algorithm for imitating different animal gaits without expensive simulation training or real-world fine-tuning. Our method consists of stance and swing leg controllers using a centroidal dynamics model augmented with online adaptation techniques. We also develop a whole-body trajectory optimization procedure to fix the kinematic infeasibility of the reference animal motions. We demonstrate that our universal data-driven model-based controller can seamlessly imitate various motor skills, including trotting, pacing, turning, and side-stepping. It also shows better tracking capabilities in simulation and the real world against several baselines, including another model-based imitation controller and a learning-based motion imitation technique.
