Zhecheng Yuan @fancy_yzc
PhD @Tsinghua University, IIIS. Interested in reinforcement learning, representation learning, robotics. gemcollector.github.io Joined July 2021-
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Zhecheng Yuan retweeted
Meet mjlab. Powered by MuJoCo Warp. Drops Monday.
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Zhecheng Yuan retweeted
Come by to the MuJoCo meetup at CoRL 🇰🇷. I'll be there if you want to chat! github.com/google-deepmin…
Nice work! Our recent project HERMES also leverages a similar pipeline for bimanual dexterous manipulation — using a unified reward and egocentric depth-based sim2real to deploy in diverse in-the-wild scenarios for a variety of tasks. gemcollector.github.io/HERMES/
Nice work! Our recent project HERMES also leverages a similar pipeline for bimanual dexterous manipulation — using a unified reward and egocentric depth-based sim2real to deploy in diverse in-the-wild scenarios for a variety of tasks. gemcollector.github.io/HERMES/
Zhecheng Yuan retweeted
We just did World’s first on-stage autonomous demo of long-horizon dexterous VLA 🚨 No training. No setup. Performance out of the box. Live demo is hard and unpredictable, but we felt great about our model’s generalization, and it went pretty well! 💯 Zero-shot. 100% success.
Zhecheng Yuan retweeted
solid deployment🫡
Zhecheng Yuan retweeted
Very impressive！Focused sim2real mobile dexterous manipulation，human data is leveraged for the guidance in reinforcement learning.
Very impressive！Focused sim2real mobile dexterous manipulation，human data is leveraged for the guidance in reinforcement learning.
Zhecheng Yuan retweeted
In weekly meeting, our advisor Huazhe kept asking: "What's the real point of simulation for manipulation?" HERMES offers a potential answer. Our framework converts diverse human motion data into real robot behaviors via sim training, all without task-specific reward designing.
In weekly meeting, our advisor Huazhe kept asking: "What's the real point of simulation for manipulation?" HERMES offers a potential answer. Our framework converts diverse human motion data into real robot behaviors via sim training, all without task-specific reward designing.
Zhecheng Yuan retweeted
How do we learn motor skills directly in the real world? Think about learning to ride a bike—parents might be there to give you hands-on guidance.🚲 Can we apply this same idea to robots? Introducing Robot-Trains-Robot (RTR): a new framework for real-world humanoid learning.
Very cool results! Many thanks to Yanjie for the hard work in getting my R1 Pro model dancing as well!@ZeYanjie 👏
Very cool results! Many thanks to Yanjie for the hard work in getting my R1 Pro model dancing as well!@ZeYanjie 👏
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