Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining
Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining
The paper presents HumanVerse-500, a 500-hour dataset of human loco-manipulation behaviors collected with a lightweight wearable system. It introduces λ₀, a whole-body humanoid vision-language-action policy trained through three stages, achieving state-of-the-art performance on real-world tasks and analyzing how human data supports downstream control.
Source: arXiv Robotics — research abstracts · Read original article ↗
English translation unavailable. Choose the original article to read it.
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
Reported duration
500 hours
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
a 500-hour dataset of diverse human loco-manipulation behaviors in open-world environments
Open source E1
Source：arXiv Robotics — research abstracts · arxiv.org