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/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.

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nvidia-skills
3.7k200 skills
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$ npx -y skills add NVIDIA/skills --skill isaac-humanoid-cloud-control --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/isaac-humanoid-cloud-control

Context preview

The summary Claude sees to decide when to auto-load this skill.

Run streamed Unitree G1 cloud-navigation demos in Isaac Sim with guarded gantry release. Use for demo, destination, Mission Control, or cleanup requests.

SKILL.md

isaac-humanoid-cloud-control.SKILL.md
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>"
  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](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

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