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效率与协作 · SKILL.md

simulator-foundations

simulator-foundations

【效率与协作】Use ProtoMotions simulator, robot, terrain, scene, and tutorial building blocks without jumping into full training.

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技能说明

GitHub

name: simulator-foundations description: "Use ProtoMotions simulator, robot, terrain, scene, and tutorial building blocks without jumping into full training." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

ProtoMotions simulator foundations

Use this sub-skill for tasks that ask how ProtoMotions creates simulators, loads robots, builds terrains/scenes, reads context views, or validates a robot/environment setup before training.

Read first

  • references/simulator-api.md: factories, config objects, import order, and simulator state concepts.
  • references/tutorial-map.md: progressive learning path from simulator creation to DeepMimic.
  • references/visualization.md: motion and random-pose visual checks and safety notes.
  • scripts/smoke_config_factories.py: safe script that constructs robot and simulator config objects without creating a simulator runtime.

Typical tasks

  • Choose a simulator backend for a small debug run.
  • Create a robot config with robot_config("g1"), robot_config("smpl"), or another registered name.
  • Build simulator_config(...) from a robot, backend name, headless flag, env count, and experiment name.
  • Add procedural terrain or scene objects to an environment config.
  • Understand EnvContext and MdpComponent bindings for observations/rewards/terminations.
  • Validate a custom robot's MJCF/config before training.

Safe workflow

  1. Confirm backend environment and import order using the install sub-skill.

  2. Construct configs only; do not instantiate simulator classes until backend dependencies are verified.

  3. Run a small robot/simulator config smoke:

    python scripts/smoke_config_factories.py --robot g1 --simulator mujoco --num-envs 1
    
  4. For visual checks, start with one environment, headless where possible, then enable rendering only when the display/Kit backend is ready.

  5. If changing robot assets or custom simulator adapters, prefer unit tests or factory smokes before long rollouts.

Key invariants

  • Robot configs own asset paths, body-name mappings, control gains, default root height, trackable bodies, and per-simulator physics params.
  • Simulator configs are selected by backend name and must use that robot's matching simulation params.
  • BaseEnv composes simulator, terrain, scene library, motion library, observation/reward/termination components, and control components.
  • MDP components are pure tensor functions wired to context paths plus static params.
  • Tutorial scripts are educational and backend-runnable; they are not a substitute for environment-specific install verification.
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