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CoRL 2026 Spotlight 🌟
A team from Alibaba, RUC, SJTU, BIGAI, and BUAA introduced Ego2Robot.
It turns first-person human videos into robot training data.
18,561 hours of synthetic robot data across 15 robot morphologies.
Ego2Robot tackles 3 challenges:
- Turning human hand movements into robot end-effector trajectories.
- Replacing human arms with robot arms in the original scenes.
- Filtering out low-quality or inconsistent samples.
It also supports two types of input:
• Videos with existing hand-pose annotations.
• Raw videos, where AI estimates hand poses and splits long videos into individual tasks.
On RoboTwin 2.0’s Randomized test, the robot-only model scored 50.9%.
Adding Ego2Robot data at a 1:1 ratio with real robot data raised the score to 53.5%, a 2.6 percentage-point gain.
ego-to-robot data pipeline is one key component of Qwen-RobotManip (
Today, we’re sharing the full technical details behind it: Ego2Robot 🤖
It turns egocentric human videos into scalable robot training data and improves VLA generalization across tasks and embodiments.
page:
arxiv:
huggingface upvoting 🚀: