AI RESEARCH
3D Dynamics-Aware Manipulation: Endowing Manipulation Policies with 3D Foresight
arXiv CS.CV
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ArXi:2502.10028v4 Announce Type: replace The incorporation of world modeling into manipulation policy learning has pushed the boundary of manipulation performance. However, existing efforts simply model the 2D visual dynamics, which is insufficient for robust manipulation when target tasks involve prominent depth-wise movement. To address this, we present a 3D dynamics-aware manipulation framework that seamlessly integrates 3D world modeling and policy learning. Three self-supervised learning tasks (current depth estimation, future RGB-D prediction, 3D flow prediction) are