InterReal: A Unified Physics-Based Imitation Framework for Learning Human-Object Interaction Skills
Interaction is one of the core abilities of humanoid robots. However, most existing frameworks focus on non-interactive whole-body control, which limits their practical applicability. In this work, we develop InterReal, a unified physics-based imitation learning framework for Real-world human-object Interaction (HOI) control. InterReal enables humanoid robots to track HOI reference motions, facilitating the learning of fine-grained interactive skills and their deployment in real-world settings. Within this framework, we first introduce a HOI motion data augmentation scheme with hand-object contact constraints, and utilize the augmented motions to improve policy stability under object pert...
| Authors | Dayang Liang, Yuhang Lin, Xinzhe Liu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 8 March 2026 |
| Last updated at source | 8 March 2026 |
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