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arXiv:2610.28585v1 Announce Type: cross Abstract: Simulation is a powerful tool for robotics, but building diverse, simulation-ready scenes at scale remains difficult. Reconstructing scenes from sing...
WorldMirror is a real‑to‑sim framework that builds interactive digital twins from real‑world robot demonstrations by iteratively refining an executable world program. A coding agent decomposes the observed scene, plans reconstruction steps, and coordinates image and 3D generation tools, using verification feedback to correct errors. The resulting camera‑pose‑anchored scene representation preserves spatial relationships and enables physically consistent interaction and trajectory replay, as shown on the DROID dataset.
SceneAgent is an agentic pipeline that transforms 3D and 4D visual captures—such as 3D Gaussian Splatting, photogrammetry, LiDAR, AI‑generated scenes, and dynamic 4D videos—into interactive simulation environments. It coordinates object reconstruction, physical modeling, part decomposition, articulation, and deformable simulation, and then generates diverse object variants and scripted demonstrations to support policy learning. In benchmark tests, SceneAgent outperforms SimFoundry on cluttered bin scenes and dramatically improves dynamic IoU on 4DCodeBench, while also enabling simulated interactions and preliminary real‑robot policy transfer.
Simulation-ready world reconstruction demands physical interactivity beyond visual realism, which existing black-box 3D generation fails to deliver. We present NeoWorld-3, a coding-agent framework tha...
The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual observations into simulation-ready scenes remains cha...
arXiv:2610.27690v1 Announce Type: new Abstract: Simulation-ready world reconstruction demands physical interactivity beyond visual realism, which existing black-box 3D generation fails to deliver. We...