RESEARCH PAPERSubmitted 30 Apr 2026

World Model for Robot Learning: A Comprehensive Survey

Bohan Hou; Gen Li; Jindou Jia; Tuo An; Xinying Guo; Sicong Leng; Haoran Geng; Yanjie Ze; Tatsuya Harada; Philip Torr; Oier Mees; Marc Pollefeys; Zhuang Liu; Jiajun Wu; Pieter Abbeel; Jitendra Malik; Yilun Du; Jianfei Yang

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Major category: Related resources
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Subcategories: Surveys & technical resources
Source review status: Verified from primary sources

Category review. This 2026 survey organizes learned world models for robotics by their role in prediction, simulation and policy learning. It is a modern literature resource, not a new dataset/model or pre-2026 foundation. Reading evidence

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BibTeX

@article{hou2026world,
  title={World model for robot learning: A comprehensive survey},
  author={Hou, Bohan and Li, Gen and Jia, Jindou and An, Tuo and Guo, Xinying and Leng, Sicong and Geng, Haoran and Ze, Yanjie and Harada, Tatsuya and Torr, Philip and others},
  journal={arXiv:2605.00080},
  year={2026}
}

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