LeCAR-Lab

    LeCAR-Lab/ASAP

    [RSS 2025] "ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills"

    backend
    humanoid
    reinforcement-learning
    robotics
    Python
    MIT
    2.1K stars
    194 forks
    2.1K GitHub watchers
    Updated Oct 28, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    The project lists 4 contributors on GitHub.

    Gained 29% fewer stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Align simulation and real-world physics to train agile humanoid whole-body skills using reinforcement learning.
    • Enables smooth sim2sim and sim2real policy transfer across multiple simulators and real robots with minimal code changes.
    • Use for training phase-based motion tracking policies to imitate complex humanoid motions like sports moves.
    • Use for retargeting human motion data to diverse humanoid robot models via a generic SMPL-based pipeline.
    • Use for deploying and testing learned humanoid locomotion policies on real Unitree G1 robots safely.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    MIT

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present

    Watch-outs

    • No commits in the last six months (last push Jan 2026).
    • No GitHub releases; pin a commit or tag instead of a release.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Robotics: Science and Systems (RSS) 2025

    Excerpt from the LeCAR-Lab/ASAP README on GitHub (MIT license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    194-5

    Open issues

    65+2

    Compared with peers in Backend

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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