# SMR: Learning streaming motion retargeting for humanoids from human semantics

- Source: arXiv cs.RO
- Published: 2026-10-22T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/l4du34zi6sf16qc4rvg2fr4nx
- Original: https://arxiv.org/abs/2610.29169

## Summary

SMR is a streaming neural motion retargeter learned from semantic-conditioned physics experts. It converts human motion into robot task-space targets, which the physics experts track in simulation, and then uses a strictly causal Transformer to learn their executed trajectories. Each new frame uses only current and past human observations to generate a robot motion reference for a downstream whole-body controller. Experiments show that the semantic-conditioned physics experts outperform direct-optimization retargeting in semantic fidelity and physical validity, and that the resulting streaming retargeter performs better in closed loop under a unified whole-body controller than kinematic and physics-refinement baselines.