PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation

• URL: http://arxiv.org/abs/2607.01938v1
• Date: Thu, 02 Jul 2026 09:32:39 GMT
• Title: PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation
• Abstract summary: We propose PhysMani, a framework that couples a physics-principled 3D Gaussian world model with a future-aware action policy model.<n>We introduce PhysMani-Bench, a dynamic manipulation benchmark with 16 tasks, and demonstrate a superior success rate over strong baselines in both simulation and real-world robot experiments.
• Score: 21.625914828006856
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Manipulating fast and dynamically moving targets in unstructured 3D environments remains challenging for embodied AI. Existing visual-language-action models and world models struggle with accurate 3D geometry and physically meaningful forecasting. We propose PhysMani, a framework that couples a physics-principled 3D Gaussian world model with a future-aware action policy model. The world model learns a divergence-free Gaussian velocity field via online optimization for fast and physically grounded future dynamics prediction. The policy model integrates the predicted 3D scene future dynamics through a learnable token based cross-attention module. We introduce PhysMani-Bench, a dynamic manipulation benchmark with 16 tasks, and demonstrate a superior success rate over strong baselines in both simulation and real-world robot experiments.

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