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name: robotwin description: "Use RoboTwin bimanual manipulation simulation, data, task authoring, and XPolicyLab policy-evaluation workflows." metadata: disco-role: operating disable-model-invocation: true license: MIT

RoboTwin

Use this repo skill when a user asks about RoboTwin 2.0, dual-arm/bimanual manipulation simulation, RoboTwin task configs/classes, demonstration data collection, XPolicyLab-format trajectories, or XPolicyLab policy evaluation for RoboTwin.

Start here

1. If the user already has a RoboTwin workspace, work there. If not, use the bundled workspace bootstrapper to materialize a pinned public workspace and public assets without depending on the construction checkout.
2. Check setup before long runs: Python 3.10/3.11, NumPy 1.x ABI, SAPIEN/MPLib/Open3D/PyTorch dependencies, downloaded assets, and initialized XPolicyLab submodule when evaluating policies.
3. Route to the smallest sub-skill below. Return here for cross-cutting install, assets, provenance, and global troubleshooting.

Sub-skill routes

User intent	Read
Understand Base_Task, task classes, SAPIEN scene setup, action helpers, robot/camera configs, render smoke, or planning failures	simulation-core
Download pre-collected data, collect demonstrations, validate XPolicyLab HDF5, understand data layouts, or convert legacy raw episodes	data-pipeline
Configure XPolicyLab local/remote policy evaluation, scheduler dry-runs, policy-server pools, result logs, or qpos/endpose action adapter shapes	policy-eval
Add or modify tasks/configs/language templates, expand episode instructions, or reason about credential-bound LLM/code-generation utilities	task-authoring

Cross-cutting references

• repo-provenance.md: source revision and evidence paths used to build this skill.
• install-and-submodules.md: setup sequence, dependency pins, assets, and XPolicyLab submodule handling.
• workspace-bootstrap.md: self-contained bootstrap/check/download entry point for users without a ready workspace.
• troubleshooting.md: global failures that span sub-skills.
• repo-routing-metadata.json: structured router metadata for managed repo-skill import.
• scripts/check_robotwin_prereqs.py: read-only workspace and dependency check before any mutating workflow.

Bundled runtime entry points

• scripts/robotwin_workspace.py: self-contained bootstrapper for pinned public workspaces, asset/data download, collection dispatch, and evaluation dispatch.
• scripts/check_robotwin_prereqs.py: read-only environment and workspace probe for dry-run validation before any mutating workflow.

High-level workflows

Prepare a workspace

1. If starting from scratch, run the bundled workspace bootstrapper to create a pinned public RoboTwin checkout.
2. Create an isolated Python 3.10/3.11 environment.
3. Install the simulation/data/eval dependencies with numpy==1.26.4; avoid Python 3.13 for current compiled dependencies.
4. Download and extract RoboTwin assets before importing envs or running tasks.
5. Run a SAPIEN render smoke.
6. For policy evaluation, initialize XPolicyLab or use the bootstrapper's bootstrap --with-xpolicylab path before working on adapter workflows.

Collect or inspect data

1. Use data-pipeline to choose pre-collected data vs self-collection.
2. Use simulation-core if collection fails during task initialization, actor creation, rendering, or planning.
3. Validate HDF5 schema before feeding data to training or LeRobot conversion.
4. If you only need a standalone workspace or public asset/data acquisition flow, the bundled bootstrapper can create it without any original checkout.

Evaluate a policy

1. Initialize XPolicyLab and confirm the policy adapter exists.
2. Use policy-eval for local scheduler or remote server/client commands.
3. Run dry-runs and synthetic action-shape checks before full rollout.
4. Use data-pipeline for dataset layout questions and simulation-core for environment/task failures.

Do not assume

• Do not assume RoboTwin is pip-installable as a normal package; this source revision has no setup.py or pyproject.toml.
• Do not import top-level envs before assets are present; cluttered-object metadata is read during import.
• Do not treat the empty or uninitialized XPolicyLab directory as a usable policy stack; initialize the submodule first.
• Do not run large downloads, long collection, policy rollouts, or credentialed LLM generation unless the user asks for those side effects.