About

Imported from nvidia/skills (skills/i4h-workflow-dataset-teleop/SKILL.md). Install upstream with npx skills add nvidia/skills --skill i4h-workflow-dataset-teleop. Copyright stays with the author (Apache-2.0).

Record Teleop Demonstrations

Name: i4h-workflow-dataset-teleop
Author: nvidia

Purpose

Run the workflow's declared teleop graph through the shared SimulationRunner so actions, state, cameras, segments, attempts, and outcomes use the normal HDF5 contract.

Instructions

Resolve the base checkout and live teleop device contract.
Choose a supported human-input device.
Record in the foreground through run.sh.
Inspect visible motion and HDF5 content.

Resolve support

export I4H_WORKFLOWS_REPO_URL="${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}"
I4H_REPO_DIR_NAME="${I4H_WORKFLOWS_REPO_URL%/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*:}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME%.git}"
[ -n "$I4H_REPO_DIR_NAME" ] || { echo "Cannot derive a checkout name from I4H_WORKFLOWS_REPO_URL" >&2; exit 2; }
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/i4h_workflows" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/$I4H_REPO_DIR_NAME}"
  [ -d "$ROOT/workflows/i4h_workflows" ] || git clone "$I4H_WORKFLOWS_REPO_URL" "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"
cd "$ROOT"
./run.sh list
./run.sh show <workflow> --mode teleop

Treat the resolver above as part of the skill contract: a hosted copy may run outside the base repository, so never assume the current checkout contains workflows/i4h_workflows. I4H_WORKFLOWS_REPO_URL selects the clone source. When I4H_WORKFLOWS is unset, derive the fallback directory from that URL; set I4H_WORKFLOWS only to reuse or choose a specific destination. Never replace an existing checkout.

Require teleop in the live mode list. Read the workflow builder, its scene manifest teleop override, and the embodiment manifest's teleop_devices. Do not maintain a static support table in the skill.

Choose input

Use the named device when supported.
Otherwise use the workflow builder's default device.
Keep interactive keyboard/leader/VR/bus sessions visible and in the foreground. Surface the device controls and require the human operator to complete the task.
Never pretend to provide human input in an unattended shell.

Record

./run.sh <workflow> --teleop <device> \
  --episodes <N> --attempts 3 \
  --record

Omit <device> to use the workflow default. Bare --record writes demos.hdf5 inside the launcher's automatic run directory. Read the absolute directory from the ==> run dir ... line or run.json; do not recreate its timestamp in the shell. When a larger pipeline requires a caller-selected shared directory, pass --run-dir "$RUN_DIR" --record demos.hdf5; the launcher creates the directory and anchors the relative recording name inside it. An absolute --record path remains supported.

Verify

Require the final N/N episodes succeeded summary. Then inspect content:

RUN_DIR="<absolute run_dir from run.json or launcher output>"
uv run --project tools/dataset i4h-dataset inspect "$RUN_DIR/demos.hdf5" --segments
uv run --project tools/dataset i4h-dataset actions "$RUN_DIR/demos.hdf5"

Visually confirm that the operator completes the requested task, robot motion matches the input device, and all expected cameras record the same behavior. Treat zero saved episodes, missing observations, absent action motion, or an unsuccessful task outcome as failure. Stop leftovers with ./stop.sh all.

Troubleshooting

On device or width errors, compare the workflow teleop builder, Scene mode override, and embodiment devices.

Prerequisites

Require a workflow with teleop, a supported device, a working simulator, and a present operator for interactive input.

Limitations

Teleop records human input and requires an operator for interactive devices. Record autonomous rule-based Tasks with i4h-workflow-validate instead.

Examples

Record 5 keyboard teleop demonstrations for locomanip tray pick and place. → use G1's supported keyboard device, require a human operator, and verify the recorded action motion.

Completion gate

Report workflow, mode/device, controls, requested/saved episodes, attempts, visual result, HDF5 path, dimensions/segments, and whether a human operator completed the task.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/nvidia-skills-i4h-workflow-dataset-teleop/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

nvidia-skills-i4h-workflow-dataset-teleop.ocm.jsonjson

{
  "ocm": "1",
  "id": "nvidia-skills-i4h-workflow-dataset-teleop",
  "kind": "skill",
  "name": "i4h-workflow-dataset-teleop",
  "description": "Record demonstrations through a workflow's teleop Task into workflow HDF5. Use for keyboard, leader, VR, or bus input; do not use for policy evaluation or autonomous rule-based Tasks.",
  "publisher": "nvidia",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "data_analysis"
    ],
    "tags": [
      "skill-md",
      "isaac-for-healthcare",
      "i4h",
      "dataset",
      "teleoperation",
      "hdf5",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Record demonstrations through a workflow's teleop Task into workflow HDF5. Use for keyboard, leader, VR, or bus input; do not use for policy evaluation or autonomous rule-based Tasks."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/nvidia/skills",
      "path": "skills/i4h-workflow-dataset-teleop/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/nvidia/skills/blob/HEAD/skills/i4h-workflow-dataset-teleop/SKILL.md",
      "key": "nvidia/skills/skills/i4h-workflow-dataset-teleop/SKILL.md"
    },
    "license": "Apache-2.0"
  },
  "instructions": "# Record Teleop Demonstrations\n\n## Purpose\n\nRun the workflow's declared teleop graph through the shared `SimulationRunner` so actions, state, cameras, segments, attempts, and outcomes use the normal HDF5 contract.\n\n## Instructions\n\n1. Resolve the base checkout and live teleop device contract.\n2. Choose a supported human-input device.\n3. Record in the foreground through `run.sh`.\n4. Inspect visible motion and HDF5 content.\n\n## Resolve support\n\n```bash\nexport I4H_WORKFLOWS_REPO_URL=\"${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}\"\nI4H_REPO_DIR_NAME=\"${I4H_WORKFLO",
  "cost": {
    "context_tokens": 1059
  }
}

Fetch it by URL: GET /api/v1/registry/nvidia-skills-i4h-workflow-dataset-teleop/manifest?version=1.0.0

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