---

name: robosuite description: "Use robosuite for MuJoCo robot manipulation environments, controllers, teleoperation demos, rendering/camera workflows, and custom MJCF modeling." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

robosuite

Use this repo skill when a task involves robosuite, MuJoCo-based robot manipulation simulation, standardized environments such as Lift / Stack / PickPlace / TwoArmLift, robot/controller configuration, teleoperation demonstration data, camera rendering, domain randomization, or custom robosuite MJCF modeling.

First checks

1. Read references/repo-provenance.md before trusting the skill against a different checkout or package version.
2. Read references/quickstart-and-installation.md for install choices, optional dependencies, and minimal smokes.
3. Run scripts/check_install.py when the environment might be broken.
4. Run scripts/inspect_registry.py when you need the available task, robot, gripper, base, or controller names.

Minimal import check:

python - <<'PY'
import robosuite as suite
print(suite.__version__)
print(sorted(suite.ALL_ENVIRONMENTS)[:5])
print(sorted(suite.ALL_ROBOTS)[:5])
PY

Minimal headless environment check:

python scripts/check_install.py --skip-optional-imports

For camera observations on headless Linux, prefer:

MUJOCO_GL=egl python scripts/check_install.py --camera-smoke true

Route by task

User task	Read next
Create a standard env, choose robots, set env_configuration, step a random policy, inspect observations/rewards, wrap with Gymnasium	sub-skills/environments/SKILL.md
Load/validate controller configs, inspect action splits, build action vectors, choose robot/gripper/base registries, extend third-party controllers	sub-skills/controllers/SKILL.md
Teleoperate with Keyboard/SpaceMouse/DualSense/MJGUI, collect demos, inspect or replay demo.hdf5, use DataCollectionWrapper or DemoSamplerWrapper	sub-skills/teleoperation/SKILL.md
Configure renderer backends, camera RGB/depth/segmentation observations, camera transforms, offscreen video, domain randomization, sensor corruption, USD notes	sub-skills/rendering/SKILL.md
Add custom envs, compose MJCF worlds/tasks/objects/arenas, validate custom robot XML, compile MJCF, choose maintainer tests	sub-skills/modeling/SKILL.md

Shared references

• references/api-registry.md lists verified registries, public signatures, wrappers, and helper APIs.
• references/troubleshooting.md covers cross-cutting install/import/controller/rendering/teleop/modeling symptoms.
• references/repo-routing-metadata.json is structured metadata for repo-skills-router import.

Optional capability policy

The core verified scope covers built-in robosuite environments, robots, controllers, wrappers, headless environment creation, and EGL offscreen camera observations.

Treat these as optional or environment-dependent unless the user explicitly installs and verifies them:

• robosuite_models for extra external robots/models
• mink==0.0.5 for the optional WholeBodyMinkIK example
• hidapi plus physical SpaceMouse or DualSense devices
• display-backed mjviewer / OpenCV viewer operation
• usd-core, Isaac Sim, Isaac Lab, Omniverse, or Blender USD rendering

Safe defaults

• Start headless with has_renderer=False, has_offscreen_renderer=False, use_camera_obs=False until the base environment works.
• Add camera observations only after setting has_offscreen_renderer=True and choosing a MuJoCo GL backend when headless.
• Use load_composite_controller_config(robot="Panda") or controller="BASIC" before writing custom JSON.
• Print action splits before constructing manual action vectors.
• Prefer state playback over action playback for exact demonstration reproduction.
• Validate edited MJCF XML before widening to full env tests.

Do not use this skill for

• generic RL algorithm implementation that does not depend on robosuite APIs
• physical robot control outside robosuite simulation
• pure MuJoCo XML work with no robosuite models/tasks/controllers
• Isaac Sim-only workflows that do not pass through robosuite export utilities