RoboDream: Compositional World Models for Scalable Robot Data Synthesis
- Published
- Source
- arXiv
- Paper number
- 287
- Field
- Robotics
- arXiv ID
- 2606.02577
Key points
- This paper proposes a generalizable body-centric world model that achieves scalable data generation by synthesizing realistic demonstrations in new objects, new scenes, and new viewpoints.
- The approach anchors generation to rendered robot motions while conditioning on explicit scene and object priors, effectively separating trajectory execution from environment synthesis.
- Real-world experiments show that the generated data consistently improves downstream policy performance across diverse manipulation tasks and substantially reduces the need for real-world data.
Paper links
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