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Rhythm: Learning Interactive Whole-Body Control for Dual ...
[Submitted on 3 Mar 2026 (v1), last revised 10 Sep 2026 (this ve · 2026-03-03 · via cs.RO updates on arXiv.org

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Abstract:Realizing interactive whole-body control for multi-humanoid systems is critical for unlocking complex collaborative capabilities in shared environments. Although recent advancements have significantly enhanced the agility of individual robots, bridging the gap to physically coupled multi-humanoid interaction remains challenging, primarily due to severe kinematic mismatches and complex contact dynamics. To address this, we introduce Rhythm, the first unified framework enabling real-world deployment of dual-humanoid systems for complex, physically plausible interactions. Our framework integrates three core components: (1) an Interaction-Aware Motion Retargeting (IAMR) module that generates feasible humanoid interaction references from human data; (2) an Interaction-Guided Reinforcement Learning (IGRL) policy that masters coupled dynamics via graph-based rewards; and (3) a real-world deployment system that enables robust transfer of dual-humanoid interaction. Extensive experiments on physical Unitree G1 robots demonstrate that our framework achieves robust interactive whole-body control, successfully transferring diverse behaviors such as hugging and dancing from simulation to reality.

Submission history

From: Hongjin Chen [view email]
[v1] Tue, 3 Mar 2026 11:04:56 UTC (32,318 KB)
[v2] Sat, 2 May 2026 15:12:06 UTC (32,318 KB)
[v3] Thu, 10 Sep 2026 10:02:30 UTC (32,318 KB)