SOURCE-LINKED INTELLIGENCE

Scaling Bimanual Household Manipulation from 1,500 hours of Demonstrations to On-Policy Corrections

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Learning generalist policies for robust bimanual manipulation is bottlenecked by the scarcity of high quality large scale human demonstration data. In this work, we release 1,500 hours of diverse bimanual manipulation demonstrations covering everyday household tasks, and use this comprehensive corpus to train XR-2, a powerful vision-language-action (VLA) model. Enabled by a purpose built high throughput data pipeline and a carefully designed multi stage training paradigm, XR-2 attains strong manipulation performance in our systematic experiments while retaining favorable training efficiency an

Read original source ↗ Open in workspace

recordType

paper

region

Global