ForeAct3D: Policy-Grounded Future World Modeling for VLA Policies
Overview
ForeAct3D enables accurate prediction of future 3D scenes through policy-grounded modeling, achieving 98.3% success on LIBERO and 37.8% in real-world tasks via semantic 3D supervision and physical consistency.
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“ver the base policy. The project page and code are available at https://github.com/anthonytao80-crypto/ForeAct3D.”
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- arXiv Robotics — research abstractsSignalForeAct3D: Policy-Grounded Future World Modeling for VLA Policies
This paper presents ForeAct3, a framework for policy-grounded future world modeling within VLA policies. It uses learnable geometric queries to decode depth, semantic segmentation, and camera pose from policy representations, enabling accurate prediction of future 3D scene states. The method improves manipulation performance through semantic 3D supervision, physical consistency, and action conditioning, achieving 98.3% average success on LIBERO and 37.8% success in real-world tasks.
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