isaac-humanoid-cloud-control
Run streamed Unitree G1 cloud-navigation demos in Isaac Sim with guarded gantry release.
Skill by yuzho <yuzho@nvidia.com>
Install
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About
Use cases: cloud-management
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/isaac-humanoid-cloud-control
What's inside
- Skill name
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>
- Instructions
- 226 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (50)
- BENCHMARK.md
- SKILL.md
- browser-viewer.compose.yaml · assets/
- carter_warehouse_navigation.png · assets/
- carter_warehouse_navigation.yaml · assets/
- skillspector-baseline.yaml · config/
- evals.json · evals/
- evals.json.license · evals/
- extension.toml · extensions/humanoid_cloud_control.autoplay/config/
- __init__.py · extensions/humanoid_cloud_control.autoplay/humanoid_cloud_control/autoplay/
- extension.py · extensions/humanoid_cloud_control.autoplay/humanoid_cloud_control/autoplay/
- bootstrap.md · references/
- README.md · references/bring-up-cloud-stack/
- run.py · references/bring-up-cloud-stack/scripts/
- README.md · references/change-fleet-composition/
- run.py · references/change-fleet-composition/scripts/
- README.md · references/change-map/
- run.py · references/change-map/scripts/
- cloud-workspace.md · references/
- dependencies.md · references/
- README.md · references/isaac-ros-activate/
- run.py · references/isaac-ros-activate/scripts/
- isaac-ros-setup.md · references/
- README.md · references/isaac-sim-installation/
- README.md · references/isaac-sim-remote/
- run.py · references/isaac-sim-remote/scripts/
- ordered-startup.md · references/
- release-4.6.md · references/
- README.md · references/submit-and-monitor-mission/
- teardown.md · references/
- troubleshooting.md · references/
- check_runtime.py · scripts/
- doctor.py · scripts/
- guarded_gantry_release.py · scripts/
- http_transport.py · scripts/
- play_viewer.py · scripts/
- preflight.py · scripts/
- prepare_cli_repository.py · scripts/
- scene_inventory.py · scripts/
- simulation_identity.py · scripts/
- submit_navigation_mission.py · scripts/
- suggest_navigation_missions.py · scripts/
- dependency_manifest.py · shared/
- simulation_gate.py · shared/
- skill-card.md
- skill.oms.sig
- test_dependencies.py · tests/
- test_io_boundaries.py · tests/
- test_security_gates.py · tests/
- upstream-versions.lock.json
SKILL.md (first lines)
# 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](references/release-4.6.md) 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](references/bootstrap.md) on a fresh host.
If the CLI or its Docker environment is missing, follow
[CLI installation and Docker setup](references/isaac-ros-setup.md), 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:=false` and
`use_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](scripts/guarded_gantry_release.py),
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_ID` for 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](assets/carter_warehouse_navigation.png)
supplies obstacle and free-space pixels for the navigation map; its
[YAML metadata](assets/carter_warehouse_navigation.yaml) 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_WORKSPACE` using
[the cloud workspace procedure](references/cloud-workspace.md). 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](references/dependencies.md) 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](upstream-versions.lock.json).
Adapter contracts: [cloud](references/bring-up-cloud-stack/README.md),
[map](references/change-map/README.md),
[fleet](references/change-fleet-composition/README.md),
[scene](references/isaac-sim-remote/README.md), and
[installation handoff](references/isaac-sim-installation/README.md), and
[ROS activation](references/isaac-ros-activate/README.md), and
[mission verification](references/submit-and-monitor-mission/README.md).
Resolve dependencies before host preflight; resolution does not launch services:
```bash
python3 "${SKILL_DIR}/scripts/doctor.py" dependencies
```From NVIDIA/skills, CC-BY-4.0 AND Apache-2.0.
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Signals
- Stars
- 3,718
- Forks
- 457
- Open issues
- 8
- Last commit (this folder)
- Oct 22, 2026 (6 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- CC-BY-4.0 AND Apache-2.0
- Repository
- github.com/NVIDIA/skills
- Website
- docs.nvidia.com/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Cite this page
isaac-humanoid-cloud-control skill. Agent Mart. https://agentmart.dev/skills/nvidia-isaac-humanoid-cloud-control (last updated 2026-10-24)