isaac-humanoid-cloud-control
Run streamed Unitree G1 cloud-navigation demos in Isaac Sim with guarded gantry release. Use for demo, destination, Mission Control, or cleanup requests.
Install / Use
npx skills add NVIDIA/skills --skill isaac-humanoid-cloud-controlInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of isaac-humanoid-cloud-control
isaac-humanoid-cloud-control scores 92/100 on our quality scale, 870th of 2,908 Automation skills we index (top 30%).
Its SKILL.md is 13 KB long, well organised into 15 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 29 days ago, so isaac-humanoid-cloud-control is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-10-23. Automated pattern scan on 2026-10-23. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
isaac-humanoid-cloud-control compared with similar skills
All 4 of these similar skills score higher than isaac-humanoid-cloud-control; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| isaac-humanoid-cloud-control (this skill)by NVIDIA | 92 | 3.4k | 29d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 101.1k | 2d ago | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 89.2k | today | MCP Server |
| rufloby ruvnet | 100 | 78.5k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 30d ago | SKILL.md |
Frequently asked questions
- How do I install isaac-humanoid-cloud-control?
- Run
npx skills add NVIDIA/skills --skill isaac-humanoid-cloud-control. The install tabs above show the steps for each supported agent. - Which AI agents does isaac-humanoid-cloud-control work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is isaac-humanoid-cloud-control safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is isaac-humanoid-cloud-control still maintained?
- The repository was last updated 29 days ago, so isaac-humanoid-cloud-control is actively maintained.
Skill content
View source on GitHubname: isaac-humanoid-cloud-control description: Run streamed Unitree G1 cloud-navigation demos in Isaac Sim with guarded gantry release. Use for demo, destination, Mission Control, or cleanup requests. license: CC-BY-4.0 AND Apache-2.0 metadata: author: "yuzho yuzho@nvidia.com" tags: - isaac-ros - isaac-sim - humanoid-navigation - mission-control
Isaac Humanoid Cloud Control
Purpose
Run the public NVIDIA Isaac ROS release-4.6 Unitree G1 cloud-control workflow as an ordered integration. Default to the Isaac Sim full streaming app running headless, an interactive browser WebRTC view, and a navigation mission. Do not silently fall back to a local Isaac Sim window. Read the release-4.6 runbook before executing the workflow.
Inputs
Required inputs are the request mode (bring-up, end-to-end demo, destination, or cleanup) and, before mission submission, an operator-supplied destination and movement approval. A selected suggestion supplies both for simulation. Remote missions also require confirmation that the rendered viewport is visible.
Optional or discoverable inputs are robot identity (g1_0 by default), hosts,
spawn pose, map, and installation paths. Resolve them from active demo state,
explicit operator choices, live observations, discovered installations, then
packaged defaults. Never let a default override an explicit safety boundary.
Prerequisites
Require an x86_64 NVIDIA GPU with NVENC, Isaac Sim 6.0, the canonical Docker-mode Isaac ROS workspace, NVIDIA's official web viewer, and the release-4.6 cloud images. Use the bootstrap gate on a fresh host. If the CLI or its Docker environment is missing, follow CLI installation and Docker setup, then rerun preflight. Missing CLI installation is a recovery step, not a terminal blocker.
Preserve the target boundary
- Require an NVIDIA GPU with NVENC for the default livestream. Preflight TCP 49100 for WebRTC signaling, UDP 47998 for media, and TCP 8210 for the browser viewer. Keep the endpoints on a private or otherwise trusted network; they provide no authentication or encryption by themselves.
- Use the owning cloud skill's broker authentication configuration and supply matching credentials to the G1 client. Keep broker ports on the host or a trusted private network; authentication alone does not provide TLS.
- Enable Isaac Sim's Python server only for live scene inventory. Keep it on loopback at 127.0.0.1:8226; it executes Python and must never be published, proxied, or exposed to the browser network.
- Use an x86_64 NVIDIA GPU host and Isaac Sim 6.0 for the sample simulation.
- Support navigation through cloud control in Isaac Sim.
- For Isaac Sim-only navigation, use
enable_camera_localization:=falseanduse_static_tf:=true. Do not launch, configure, validate, or require Visual SLAM, visual global localization, RealSense, D435, or camera-localization topics; they are outside this simulated-demo path. - Do not submit humanoid_manipulation objectives to Isaac Sim. GR00T cloud manipulation is real-hardware-only in this release.
- Treat real G1 operation as a separate safety-gated path. Require the Unitree network setup, D435 localization, CUDA MPS, real-time scheduling, and the lower-body-then-upper-body controller enable sequence from the upstream GR00T guide. Never infer permission to move real hardware.
- Submit a navigation mission only after the operator has supplied the target and explicitly approved the previewed mission payload. Verify occupancy, robot-footprint clearance, and Nav2 reachability before submission. A target selection alone is insufficient; changed routes require a new approved preview.
- Before invoking the guarded helper, obtain explicit operator approval for that virtual gantry release attempt. A broad demo request is insufficient. State the simulation target and action; ask “Release the Isaac Sim virtual gantry now?” unless the operator already explicitly approved this specific attempt. Pass the live simulation identity interlock and unsupported stability check before offering destinations. A retry needs separate explicit approval after reporting the failed attempt and confirmed gantry re-engagement. Never apply this automation to hardware. Honor an operator's request to use the viewport G action instead.
- Keep one robot identity everywhere. Default to g1_0; apply the same value to Mission Control, serial_number, MQTT topics, mission payloads, and lifecycle verification.
- Use one dedicated, initially empty
ROS_DOMAIN_IDfor Isaac Sim and every ROS shell in a demo. Set localhost-only discovery for all demo processes as specified in the ordered startup. Confirm that the clock and robot-description ROS topics are absent on that domain before startup. This prevents transient-local samples from a previous crashed run from racing the new controller manager. - The bundled occupancy-grid PNG supplies obstacle and free-space pixels for the navigation map; its YAML metadata defines the map scale and origin. The cloud workspace procedure copies this pair into the runtime workspace. These are map data, not executable instructions.
- Keep one occupancy map everywhere. The robot launch and Mission Control must consume the same PNG and YAML pair.
- Ensure the map YAML and referenced image are readable at the same absolute path inside the activated Isaac ROS environment; host-only paths are insufficient.
- Create a dedicated runtime
MC_WORKSPACEusing the cloud workspace procedure. Generate map and fleet configuration through the owning adapters. Resolve Compose, image references, and supporting resources from the pinned upstream skills; never modify their checkouts or store generated configuration in this package.
Resolve upstream scripts
Set SKILL_DIR to the absolute directory containing this loaded skill manifest,
using the skill loader's location, and preserve it in every shell invocation.
All bundled paths are relative to it; never derive them from the working directory.
Read the dependency workflow before calling another
skill's scripts. It follows the Mission Control showcase composition model:
pinned external checkouts, a persisted manifest, and parent-owned adapters.
Read each pinned upstream instruction manifest from the resolved dependency
record and follow its gates. The exact source paths and commits are disclosed in
the dependency lock.
Adapter contracts: cloud,
map,
fleet,
scene, and
installation handoff, and
ROS activation, and
mission verification.
Resolve dependencies before host preflight; resolution does not launch services:
python3 "${SKILL_DIR}/scripts/doctor.py" dependencies
Normal invocation never downloads missing skills. Explicit dependency preparation
uses dependencies --prepare only after authorization as described in the
reference. Use the linked adapters instead of guessed upstream script paths.
Compose the owning skills
Follow owning-skill responsibilities for each handoff; the upstream skill remains authoritative.
Available Scripts
| Script | Purpose | Main arguments |
| --- | --- | --- |
| scripts/doctor.py | Resolve pinned upstream scripts and write their manifest | dependencies; optional --prepare, --check-only, --json |
| scripts/prepare_cli_repository.py | Stage and verify the public APT key and fixed repository source without root | No arguments |
| scripts/preflight.py | Discover and validate host, cloud, streaming, and scene-server readiness | --map; optional installation paths and --check-* gates |
| scripts/guarded_gantry_release.py | Set AGILE, verify stability, release the simulated gantry, and verify unsupported balance | --allow-simulation-gantry-release; stability limits and durations |
| scripts/check_runtime.py | Verify ROS clock, sensors, TF, and Nav2 lifecycle | --base-frame, --timeout |
| scripts/scene_inventory.py | Inventory live-stage objects without modifying USD | injected output_path, max_objects |
| scripts/suggest_navigation_missions.py | Produce occupancy- and footprint-safe object approach poses | --inventory, --map, optional robot pose |
| scripts/submit_navigation_mission.py | Preview or submit a validated Mission Control route | --host, --robot, waypoints, --validated-free-space, --submit |
| scripts/play_viewer.py | Focus the browser viewer and send Play only as a documented fallback | --url, browser and debug options |
Use run_script() for these helpers when the runtime exposes it; otherwise run
the bundled helper by its resolved absolute path without reconstructing it.
Fresh-machine bootstrap gate
For a fresh host, read the bootstrap gate, run its read-only discovery first, and resolve failures in the documented ownership order. Continue only after preflight has no blocking failures. Report the exact failed observation rather than claiming a live view is available.
Instructions
Read and follow the ordered startup and mission workflow in full before executing. It contains the exact commands and phase gates:
- Discover host paths and inspect existing state read-only; resolve upstream dependencies before host preflight.
- Prepare the release package and Deploy extension, and preview and apply requested map and fleet changes through the owning adapters.
- Start cloud services through the cloud adapter, with the runtime workspace and no generic robot simulator.
- Prepare the official browser viewer and publish its reachable URL.
- Launch rendered headless Isaac Sim paused, stage the activated G1 ROS launch, then start the timeline and ROS stack in the required order.
- Verify AGILE and run the guarded simulation-only gantry release. Require unsupported balance before inventorying or offering destinations.
- Verify runtime and cloud readiness; inventory the live scene through the remote adapter and validate navigation suggestions with occupancy and Nav2.
- After destination approval, validate and submit once, keep the live view visible, and apply submit-and-monitor-mission until completion.
The detailed workflow is mandatory; this index does not replace its commands, startup timing, retry limits, or authorization boundaries.
Troubleshooting
Apply the readiness and troubleshooting checklist before submission and when diagnosing a failed gate.
Examples
- “Run an end-to-end humanoid cloud-control Isaac Sim demo” starts setup; obtain explicit virtual gantry release approval before running the helper.
- “Destination 1: forklift” after live suggestions selects the target. Validate the route, preview the mission payload, and obtain submission approval.
- “Bring up the stack for inspection” does not authorize gantry release or a mission.
- “Clean up the stack” authorizes teardown of demo-owned resources only.
- “Use GR00T to manipulate a box in Isaac Sim” is outside this release; offer supported navigation without inventing manipulation support.
Output Format
Report these fields in order when applicable:
- State — current phase or first failed gate with measured e
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
