{"ID":6138285,"CreatedAt":"2026-07-09T01:07:32.349475501Z","UpdatedAt":"2026-07-11T14:19:21.478473819Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.07459","arxiv_id":"2607.07459","title":"EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI","abstract":"We present EmbodiedGen V2, a generative 3D world engine for building executable sim-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapidly, yet assembling such assets into policy-ready task environments remains largely manual, limiting scalable closed-loop learning. EmbodiedGen V2 addresses this gap through a unified sim-ready representation that connects cross-simulator assets, interaction affordances, task-driven worlds, large-scale multi-room scenes, and stateful Vibe Coding into a generative, editable, and reusable simulation pipeline. The generated environments support manipulation, navigation, mobile manipulation, cross-simulator deployment, and embodied policy training. In evaluation, the asset pipeline achieves 96.5% human acceptance and 98.6% collision success, and 83.3% of task-driven worlds are directly usable for downstream simulation without manual modification. Online reinforcement learning with generated environments further improves simulation success from 9.7% to 79.8%, and transfers to real robots with task success increasing from 21.7% to 75.0%. These results establish EmbodiedGen V2 as scalable simulation infrastructure for training, evaluating, and deploying embodied policies.","short_abstract":"We present EmbodiedGen V2, a generative 3D world engine for building executable sim-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapidly, yet assembling such assets into policy-ready task environments remains largely manual, limiting scalable closed-loop learning. EmbodiedGen...","url_abs":"https://arxiv.org/abs/2607.07459","url_pdf":"https://arxiv.org/pdf/2607.07459v1","authors":"[\"Xinjie Wang\",\"Liu Liu\",\"Taojun Ding\",\"Andrew Choi\",\"Chaodong Huang\",\"Mengao Zhao\",\"Ziang Li\",\"Jackson Jiang\",\"Chunlei Yu\",\"Shengxiang Liu\",\"Wei Xu\",\"Zhizhong Su\"]","published":"2026-07-08T14:27:31Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.CV\"]","methods":"[\"Reinforcement Learning\"]","has_code":false}