PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation
World action models jointly learn to forecast world dynamics and predict robot actions, such that the learned internal world dynamics guide accurate actions. Existing approaches typically represent the world as RGB frames or latent counterparts while predicting actions as end-effector poses or joint angles, but they often struggle to capture the 3D spatial structure and contact geometry central to dexterous manipulation. We introduce Point World Action Model (PointWAM), a 3D world action model that decomposes the world into a scene (i.e., environment) and hands (i.e., actor), and jointly forecasts both as 3D point trajectories within a shared space-time coordinate frame. This explicit, di...
| Authors | Chunghyun Park, Beomjun Kim, Seungcheol Park et al. |
|---|---|
| Primary category | cs.RO |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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