X-Loco: 協調的ポリシー蒸留による汎用人型ロコモーション制御
X-Loco: Towards Generalist Humanoid Locomotion Control via Synergetic Policy Distillation
複数の専門家ポリシーを蒸留し、転倒復帰から地形走破、全身協調までを単一の視覚ベース人型ロコモーションポリシーとして学習させるフレームワークを提案。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Dewei Wang, Xinmiao Wang, Chenyun Zhang, Jiyuan Shi, Yingnan Zhao, Chenjia Bai, Xuelong Li
分類: cs.RO
原文アブストラクト
While recent advances have demonstrated strong performance in individual humanoid skills such as upright locomotion, fall recovery and whole-body coordination, learning a single policy that masters all these skills remains challenging due to the diverse dynamics and conflicting control objectives involved. To address this, we introduce X-Loco, a framework for training a vision-based generalist humanoid locomotion policy. X-Loco trains multiple oracle specialist policies and adopts a synergetic policy distillation with a case-adaptive specialist selection mechanism, which dynamically leverages multiple specialist policies to guide a vision-based student policy. This design enables the student to acquire a broad spectrum of locomotion skills, ranging from fall recovery to terrain traversal and whole-body coordination skills. To the best of our knowledge, X-Loco is the first framework to demonstrate vision-based humanoid locomotion that jointly integrates upright locomotion, whole-body coordination and fall recovery, while operating solely under velocity commands without relying on reference motions. Experimental results show that X-Loco achieves superior performance, demonstrated by tasks such as fall recovery and terrain traversal. Ablation studies further highlight that our framework effectively leverages specialist expertise and enhances learning efficiency.
