二人で成し遂げる:ヒューマノイドロボット間のインタラクティブ全身制御の学習
It Takes Two: Learning Interactive Whole-Body Control Between Humanoid Robots
二人のヒューマノイドが相互作用する人間の動作を模倣するため、接触を考慮した動作リターゲティングと相互作用駆動型制御器を組み合わせたフレームワークHarmanoidを提案。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
5. 議論はある?
6. 次に読むべき論文は?
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Zuhong Liu, Junhao Ge, Minhao Xiong, Jiahao Gu, Bowei Tang, Wei Jing, Siheng Chen
分類: cs.RO, cs.MA
原文アブストラクト
The true promise of humanoid robotics lies beyond single-agent autonomy: two or more humanoids must engage in physically grounded, socially meaningful whole-body interactions that echo the richness of human social interaction. However, single-humanoid methods suffer from the isolation issue, ignoring inter-agent dynamics and causing misaligned contacts, interpenetrations, and unrealistic motions. To address this, we present Harmanoid , a dual-humanoid motion imitation framework that transfers interacting human motions to two robots while preserving both kinematic fidelity and physical realism. Harmanoid comprises two key components: (i) contact-aware motion retargeting, which restores inter-body coordination by aligning SMPL contacts with robot vertices, and (ii) interaction-driven motion controller, which leverages interaction-specific rewards to enforce coordinated keypoints and physically plausible contacts. By explicitly modeling inter-agent contacts and interaction-aware dynamics, Harmanoid captures the coupled behaviors between humanoids that single-humanoid frameworks inherently overlook. Experiments demonstrate that Harmanoid significantly improves interactive motion imitation, surpassing existing single-humanoid frameworks that largely fail in such scenarios.
