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Sirui Chen
@eric_srchen
PhD in Stanford CS, Prev Undergrad at HKU. Interested in robotics
Stanford, CA
Joined September 2023
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  • Pinned
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    Sirui Chen
    @eric_srchen
    Jun 29
    Humanoids excel in free space but struggle with real-world contact. Meet SceneBot 🤖 the first unified RL framework for ALL free-space locomotion, terrain traversal and object interaction! By conditioning on per-link contact labels, it masters complex, interaction-rich tasks like
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    Sirui Chen
    @eric_srchen
    Jul 3
    When humanoids have all features that other platform have but have advantage that other platform don't, the benefit of humanoids shall stand out without doubt
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    Qingzhou Lu
    @Axell_wppr
    Jul 3
    Humanoids should take on the heavy lifting jobs for humans. But can full-size humanoids handle heavy-payload teleoperation from noisy VR inputs? Excited to introduce our work, HEFT: Heavy-Payload Full-size Humanoid Teleoperation. HEFT tracks human intent from raw, noisy VR
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    Sirui Chen
    @eric_srchen
    Jul 1
    For many tasks, data demand is high, but teleop is hard. We propose VLK, the first whole-body humanoid VLA policy trained solely on synthetic data. We show that it can autonomously navigate and perform object pick-and-place using language commands.
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    Jiaman Li
    @jiaman01
    Jul 1
    🤖 How can we scale up humanoid robot learning? Introducing 🌟VLK🌟: generating large-scale synthetic data with paired egocentric observations, text, and full-body G1 kinematics for learning humanoid loco-manipulation. No teleoperation needed! Website: vision-language-kinematics.github.io
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    Sirui Chen
    @eric_srchen
    Jun 5
    As dexterous hand become more human like , using human data also become easier than ever, we explore how to cotrain with both human and robot data and generalize to new task with only human data.
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    Ji Woong Kim
    @jwbkim
    Jun 5
    We show that robots can learn high-level task semantics, such as sorting rules, skill composition, and rule-based ordering, directly from human demos. This is useful because if your target task is a composition of the robot's existing skills, you could just collect human demos
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