How to Set Up NVIDIA Isaac Sim: A Practical Guide

TL;DR

• Install Isaac Sim via Omniverse Launcher on Ubuntu 22.04 with an RTX GPU
• Import robots using USD/URDF files and configure PhysX for realistic physics
• Use Replicator for synthetic data generation with domain randomization
• Bridge to ROS 2 Humble via isaac_ros packages
• Run headless on cloud instances with Omniverse Nucleus

1. Installation and System Requirements

Hardware Requirements

Isaac Sim requires:

• GPU: NVIDIA RTX 30/40 series or A100/H100 (minimum RTX 2080 Ti)
• CPU: 8+ cores (Intel Xeon/AMD Ryzen recommended)
• RAM: 32GB+ (64GB for large scenes)
• Storage: 20GB+ SSD (NVMe preferred)

Software Prerequisites

# Ubuntu 22.04 (tested)
sudo apt update
sudo apt install -y nvidia-driver-535 nvidia-cuda-toolkit
sudo apt install -y ros-humble-desktop ros-humble-isaac-ros

Installation Steps

1. Download Omniverse Launcher

   wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
   sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
   sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub
   sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"
   sudo apt update
   sudo apt install -y nvidia-omniverse-launcher
   

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2. Install Isaac Sim via Launcher

   • Open Omniverse Launcher
   • Go to Exchange → Search "Isaac Sim" → Install 2023.1.1 (latest stable)

3. Verify Installation

   ./isaac-sim.sh
   

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   Expected output:

   [Isaac Sim] Starting...
   [Omniverse Kit] Launching...
   

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Common Installation Errors

• Error: Failed to initialize CUDA Fix: Ensure NVIDIA drivers are installed:

  nvidia-smi
  

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  Should show GPU info without errors.

• Error: Missing ROS 2 Humble dependencies Fix: Install ROS 2 Humble:

  sudo apt install ros-humble-isaac-ros
  source /opt/ros/humble/setup.bash
  

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2. Importing Robots and USD Scenes

Supported File Formats

Importing a URDF Robot (Example: Franka Emika Panda)

1. Download Franka URDF

   mkdir -p ~/isaac_sim_ws/src
   cd ~/isaac_sim_ws/src
   git clone https://github.com/ros-industrial/franka_ros.git
   colcon build --symlink-install
   

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2. Convert URDF to USD

   ros2 run urdf_to_usd urdf_to_usd --input franka_ros/urdf/franka_panda.urdf --output franka_panda.usd
   

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3. Load in Isaac Sim

   • Launch Isaac Sim:

     ./isaac-sim.sh
     

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   • In the Isaac Sim UI:
     • Go to File → Import Scene
     • Select franka_panda.usd
     • Click Open

Configuring Robot Joints and Sensors

Edit the USD file to add sensors (e.g., cameras, IMUs):

def Camera "right_hand_camera" (
    xformOp:transform = @right_hand_camera_xform
    sensor:camera = {
        focalLength = 24.0
        horizontalAperture = 10.0
        clippingRange = (0.01, 100.0)
    }
)

3. PhysX Simulation and Sensor Models

Configuring Physics Properties

Edit the robot’s USD file to adjust physics:

def Xform "panda_link0" (
    xformOp:transform = @panda_link0_xform
    physics:collisionApproxConvexHull = {
        approxConvexHull = true
        collisionEnabled = true
    }
    physics:rigidBody = {
        mass = 0.5
        enableGravity = true
    }
)

Enabling Realistic Sensors

1. Add a Camera Sensor

   def Camera "head_camera" (
       xformOp:transform = @head_camera_xform
       sensor:camera = {
           focalLength = 16.0
           horizontalAperture = 8.0
           clippingRange = (0.01, 50.0)
           resolution = (640, 480)
       }
   )
   

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2. Enable Depth Sensors

   # In a Python script (e.g., `simulation_app.py`)
   from omni.isaac.sensor import Camera
   camera = Camera(prim_path="/World/head_camera", resolution=(640, 480))
   camera.enable_depth()
   

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Domain Randomization for Sim-to-Real

Use Isaac Sim’s Replicator for domain randomization:

from omni.isaac.replicator import ReplicatorClient

# Initialize Replicator
replicator = ReplicatorClient()

# Define randomization parameters
randomization_params = {
    "physics": {
        "friction": {"min": 0.1, "max": 0.9},
        "mass": {"min": 0.5, "max": 2.0}
    },
    "lighting": {
        "intensity": {"min": 0.5, "max": 2.0}
    }
}

# Apply to a scene
replicator.randomize_scene(randomization_params)

4. Synthetic Data Generation with Replicator

Generating RGB-D Datasets

1. Create a Replicator Pipeline

   from omni.isaac.replicator import ReplicatorClient, Pipeline
   
   # Initialize
   replicator = ReplicatorClient()
   
   # Define pipeline
   pipeline = Pipeline()
   pipeline.add(Pipeline.create_camera_sensor("rgb_camera", resolution=(1280, 720)))
   pipeline.add(Pipeline.create_camera_sensor("depth_camera", resolution=(1280, 720), depth=True))
   
   # Add randomization
   pipeline.add(Pipeline.randomize_physics(friction=(0.1, 0.9)))
   
   # Export data
   pipeline.add(Pipeline.write_to_disk("/data/rgb", format="png"))
   pipeline.add(Pipeline.write_to_disk("/data/depth", format="exr"))
   

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2. Run the Pipeline

   python3 replicator_pipeline.py --headless
   

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Expected Output

/data/
├── rgb/
│   ├── frame_000001.png
│   ├── frame_000002.png
│   └── ...
└── depth/
    ├── frame_000001.exr
    ├── frame_000002.exr
    └── ...

5. ROS 2 Bridge Integration

Bridging Isaac Sim to ROS 2 Humble

1. Install ROS 2 Humble Bridge

   sudo apt install ros-humble-isaac-ros-bridge
   

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2. Launch the Bridge

   ros2 launch isaac_ros_bridge isaac_ros_bridge.launch.py
   

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3. Publish a Joint State Topic

   # In a Python script (e.g., `joint_publisher.py`)
   from isaac_ros_bridge import IsaacRosBridge
   bridge = IsaacRosBridge()
   bridge.publish_joint_states("/franka_panda/joint_states")
   

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4. Subscribe to a ROS 2 Topic

   ros2 topic echo /franka_panda/joint_states
   

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Common ROS 2 Issues

• Error: TF transform failed Fix: Ensure robot_state_publisher is running:

  ros2 run robot_state_publisher robot_state_publisher --ros-args -p use_sim_time:=true
  

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• Error: No such node /isaac_ros_bridge Fix: Verify the bridge is launched:

  ros2 node list
  

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6. Headless Runs and Cloud Deployment

Running Isaac Sim Headless

./isaac-sim.sh --headless --no-window --no-gui

Deploying to AWS Cloud

1. Launch an EC2 Instance

   • Use g5.2xlarge (NVIDIA T4 GPU) or g5.4xlarge (RTX 6000 Ada).
   • AMI: Deep Learning AMI (Ubuntu 22.04).

2. Install Isaac Sim on AWS

   # Follow the same installation steps as above
   wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
   sudo apt install -y nvidia-omniverse-launcher
   

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3. Run Headless Simulation

   nohup ./isaac-sim.sh --headless --no-window --no-gui > simulation.log 2>&1 &
   

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Using Omniverse Nucleus for Multi-User Collaboration

1. Start Nucleus Server

   omniverse-nucleus-server --headless --port 3000
   

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2. Connect Clients

   ./isaac-sim.sh --nucleus-host <AWS_IP> --nucleus-port 3000
   

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What’s Next?

1. Test Your Setup: Run a simple pick-and-place task using Isaac Sim’s Manipulation extension.
2. Generate Synthetic Data: Use Replicator to create 10,000 RGB-D images for training.
3. Deploy to Cloud: Scale to 10+ robots using AWS EC2 G5 instances.

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