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arXiv · 2604.16903

Leveraging VR Robot Games to Facilitate Data Collection for Embodied Intelligence Tasks

Yihan Zhang·Ziyun Huang·Linqi Ye
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Abstract

Collecting embodied interaction data at scale remains costly and difficult due to the limited accessibility of conventional interfaces. We present a gamified data collection framework based on Unity that combines procedural scene generation, VR-based humanoid robot control, automatic task evaluation, and trajectory logging. A trash pick-and-place task prototype is developed to validate the full workflow.Experimental results indicate that the collected demonstrations exhibit broad coverage of the state-action space, and that increasing task difficulty leads to higher motion intensity as well as more extensive exploration of the arm's workspace. The proposed framework demonstrates that game-oriented virtual environments can serve as an effective and extensible solution for embodied data collection.

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Yihan Zhang, Ziyun Huang, Linqi Ye. 2026-04-18. Leveraging VR Robot Games to Facilitate Data Collection for Embodied Intelligence Tasks. https://arxiv.org/abs/2604.16903

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