Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking
Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity. Training such models from scratch requires large-scale data and computation, making rapid deployment on new humanoid platforms costly. This raises a natural question: Can pretrained WBT models transfer across embodiments with minimal adaptation? To answer this question, we propose Any2Any, a paradigm that efficiently transfers an existing WBT specialist to a new humanoid embodiment with only a small amount of data and compute. Any2Any first performs kinematic alignment between source and target humanoids, aligning their input and output spaces so ...
| Authors | Ming Yang, Tao Yu, Feng Li et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 May 2026 |
| Last updated at source | 18 June 2026 |
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