SOURCE-LINKED INTELLIGENCE
From Gameplay to Policy: Towards Scalable Robot Data Collection via Gamified Robot-Free Interaction
Learning generalizable robot manipulation policies requires large-scale and diverse interaction data, yet collecting real-world demonstrations remains costly and difficult to scale. Existing approaches to data collection are either dependent on specific robot hardware that limits crowdsourcing and transferability, or suffer from incomplete annotation and limited behavioral diversity. Inspired by how games sustain long-term human engagement, we explore an alternative paradigm that turns data collection into an engaging gameplay experience and transfers the resulting human manipulation experienc
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T13:33:06.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.