Robot Learning from Any Images
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Abstract (arXiv)
We introduce RoLA, a framework that transforms any in-the-wild image into an interactive, physics-enabled robotic environment. Unlike previous methods, RoLA operates directly on a single image without requiring additional hardware or digital assets. Our framework democratizes robotic data generation by producing massive visuomotor robotic demonstrations within minutes from a wide range of image sources, including camera captures, robotic datasets, and Internet images. At its core, our approach combines a novel method for single-view physical scene recovery with an efficient visual blending strategy for photorealistic data collection. We demonstrate RoLA's versatility across applications like scalable robotic data generation and augmentation, robot learning from Internet images, and single-image real-to-sim-to-real systems for manipulators and humanoids. Video results are available at https://sihengz02.github.io/RoLA .
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 55 of its 65 references that are in the map. First posted on arXiv 26 Sep 2025.
Builds on
55 of 65 references.
References · 55
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38 more
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50 most cited of 55 All 55 (JSON)
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Citing papers per year: 2025: 4; 2026: 3.
7 papers.
- 2025Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulationcited by 25
- 2025Robot Learning from a Physical World Modelcited by 20
- 2026Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Modelscited by 11
- 2025OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learningcited by 10
- 2026TTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkourcited by 4
- 2025IGen: Scalable Data Generation for Robot Learning from Open-World Imagescited by 1
- 2026GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learningcited by 1
- 2026GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learning5 Sep 2026
- 2026Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models17 Mar 2026
- 2026TTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkour2 Feb 2026
- 2025OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learning15 Dec 2025
- 2025IGen: Scalable Data Generation for Robot Learning from Open-World Images1 Dec 2025
- 2025Robot Learning from a Physical World Model10 Nov 2025
- 2025Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation9 Oct 2025