RDC_Simulation/docs/docker.md

Docker Setup for RDC Simulation

This guide explains how to run the RDC Simulation environment inside a Docker container with NVIDIA GPU support and X11 display forwarding. This approach isolates the simulation environment from your host system while providing full hardware acceleration.

Prerequisites

1. Docker Engine: Install Docker for your OS.

2. NVIDIA GPU & Drivers: Ensure you have an NVIDIA GPU and proprietary drivers installed.

3. NVIDIA Container Toolkit: Required for GPU pass-through to Docker.

   # Install NVIDIA Container Toolkit
   curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
   echo "deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/deb/$(. /etc/os-release;echo $ID$VERSION_ID) /" | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
   sudo apt update && sudo apt install -y nvidia-container-toolkit
   sudo systemctl restart docker
   

Quick Start

1. Build the Image

cd ~/RDC_Simulation
docker compose build

This may take 15-20 minutes mostly due to compiling Gazebo plugins.

2. Allow X11 Display Access

To allow the container to display the Gazebo GUI on your host screen:

xhost +local:docker

3. Run the Container

docker compose run --rm simulation

This drops you into a bash shell inside the container as the user pilot.

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Running the Simulation

Once inside the container, the environment is pre-configured.

1. Start the Environment

You can use the helper script to verify everything is ready:

./docker-entrypoint.sh

2. Launch Components (Multi-Terminal)

Since docker compose run gives you a single terminal, you can verify basic functionality, but for the full workflow you might want to run the combined script:

# Run everything (Gazebo + SITL + Controller)
./scripts/run_ardupilot_controller.sh

Or manually launch components in background/separate terminals:

To open a second terminal into the running container:

1. Find the container name or ID: docker ps
2. Exec into it: docker exec -it <container_name> bash

Then run your components:

• Terminal 1: Gazebo

  ./scripts/run_ardupilot_sim.sh runway
  

• Terminal 2: ArduPilot SITL

  sim_vehicle.py -v ArduCopter -f gazebo-iris --model JSON --console
  

• Terminal 3: Controller

  python scripts/run_ardupilot.py --pattern square
  

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Video Recording

The Docker image includes ffmpeg and tools to record the simulation.

Record Flight

Run a flight pattern and save the video automatically:

python scripts/record_flight.py --pattern square --quality high --output my_flight_video

Videos are saved to the recordings/ directory which is mounted inside the container (if you used a volume mount) or can be copied out.

Record Manually

./scripts/record_simulation.sh --duration 30

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Headless Mode (CI/Server)

If you are running on a remote server without a display attached, use the headless service. Note that standard Gazebo GUI will not show, but you can still run simulations and record videos (rendering offscreen).

docker compose run --rm simulation-headless

Troubleshooting

"All CUDA-capable devices are busy or unavailable" Check your NVIDIA drivers on the host. verifying with nvidia-smi.

"Example: Could not connect to display :0" Make sure you ran xhost +local:docker on the host machine. If using SSH, ensure X11 forwarding is enabled (ssh -X).

Persisting Data The docker-compose.yml mounts the project directory. Changes to python scripts inside the container are reflected on your host machine.