PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking
Humanoid robots are expected to execute agile and expressive whole-body motions in real-world settings. Existing text-to-motion generation models are predominantly trained on captured human motion datasets, whose priors assume human biomechanics, actuation, mass distribution, and contact strategies. When such motions are directly retargeted to humanoid robots, the resulting trajectories may satisfy geometric constraints (e.g., joint limits and pose continuity) and appear kinematically reasonable. However, they frequently violate the physical feasibility required for real-world execution. To address these issues, we present PhyGile, a unified framework that closes the loop between robot-na...
| Authors | Jiacheng Bao, Haoran Yang, Yucheng Xin et al. |
|---|---|
| Primary category | cs.RO |
| Published | 13 March 2026 |
| Last updated at source | 30 August 2026 |
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