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berkeley-humanoidsberkeley-humanoids/Skills/skills/robotics-conventions/SKILL.md

robotics-conventions

Skill4 starsChanged 34 days agoCC0-1.0View on GitHub

Robotics and robot-learning code conventions. Use when handling frames, units, axes, signs, quaternions, URDFs, sim-to-real, RL/IL policies, kinematics, hardware, visualization, or data pipelines.

1 other project uses a version of this.

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Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 1

    1. berkeley-humanoids/skills★ 4100% same

    Edited · 0

    None found.

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository8 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 5 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer explicit names in variables, methods, classes, and configs.

    line 8
  2. Very specific:

    Use _left / _right, not _l / _r.

    line 9
  3. Distinctive:

    Avoid ambiguous abbreviations unless they are standard in robotics.

    line 10
  4. Distinctive:

    Use SI units everywhere: meters, seconds, radians, kilograms, Newtons, and Newton-meters.

    line 12
  5. Very specific:

    Use scalar-first quaternion order: (qw, qx, qy, qz).

    line 16
  6. Very specific:

    Use REP-103 robot frames: x forward, y left, z up, right-handed.

    line 20
  7. Distinctive:

    Prefer realigning CAD assets or motion data during export, not patching frame conversions in runtime code.

    line 22
  8. Distinctive:

    Keep the ordering defined in one source of truth and reference it everywhere.

    line 36

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Robotics Conventions

  • Prefer explicit names in variables, methods, classes, and configs.
    • Use _left / _right, not _l / _r.
    • Avoid ambiguous abbreviations unless they are standard in robotics.
  • Use SI units everywhere: meters, seconds, radians, kilograms, Newtons, and Newton-meters.
    • Non-SI values are only allowed at third-party, UI, logging, or hardware API boundaries.
    • Mark non-SI variables with suffixes such as _deg, _ms, _mm.
  • Use scalar-first quaternion order: (qw, qx, qy, qz).
    • Normalize quaternions before storing or applying them.
    • Convert explicitly at library/message boundaries when another order is required (e.g. in ROS 2).
  • Use REP-103 robot frames: x forward, y left, z up, right-handed.
    • Blender and Onshape use y forward, z up.
    • Prefer realigning CAD assets or motion data during export, not patching frame conversions in runtime code.
  • Training environment setup should follow this order:
    • Command
    • Observation
    • Action
    • Metrics
    • Rewards
    • Terminations
    • Events
    • Curriculum
  • Robot joint ordering should follow a depth-first body traversal.
    • Example: left arm shoulder-to-hand, right arm shoulder-to-hand, left leg hip-to-foot, right leg hip-to-foot.
    • Keep the ordering defined in one source of truth and reference it everywhere.
  • For ROS 2 or ros2_control code, use the ros2-conventions skill.
  • Prefer environment managers:
    • uv for Python environments.
    • pixi for C/C++ and ROS 2 environments.
  • Preferred data formats:
    • .mcap for raw data recording, especially when interfacing with C/C++ code.
    • LeRobotDataset / .parquet for training datasets stored as Hugging Face dataset repositories.
    • .rbl for saved Rerun visualizations that combine .mcap data with a Rerun layout.
  • Preferred visualization tools:
    • Rerun for multimodal data visualization, especially when it needs custom Blueprint panels.
    • Viser for motion and pose visualization only.
    • MuJoCo for physics-based interactive visualization.

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