diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -124,6 +124,7 @@ sim_vehicle.py -v ArduCopter -f gazebo-iris --model JSON --console --wipe-eeprom
 ## Documentation
 
 - [Installation Guide](docs/installation.md)
+- [Docker Guide](docs/docker.md)
 - [ArduPilot Guide](docs/ardupilot.md)
 - [Drone Controller Guide](docs/drone_guide.md)
 - [Architecture](docs/architecture.md)
diff --git a/docs/docker.md b/docs/docker.md
new file mode 100644
index 0000000..c05d19c
--- /dev/null
+++ b/docs/docker.md
@@ -0,0 +1,126 @@
+# 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.
+
+    ```bash
+    # 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
+
+```bash
+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:
+
+```bash
+xhost +local:docker
+```
+
+### 3. Run the Container
+
+```bash
+docker compose run --rm simulation
+```
+
+This drops you into a bash shell inside the container as the user `pilot`.
+
+---
+
+## 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:
+
+```bash
+./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:
+
+```bash
+# 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
+    ```bash
+    ./scripts/run_ardupilot_sim.sh runway
+    ```
+*   **Terminal 2:** ArduPilot SITL
+    ```bash
+    sim_vehicle.py -v ArduCopter -f gazebo-iris --model JSON --console
+    ```
+*   **Terminal 3:** Controller
+    ```bash
+    python scripts/run_ardupilot.py --pattern square
+    ```
+
+---
+
+## Video Recording
+
+The Docker image includes `ffmpeg` and tools to record the simulation.
+
+### Record Flight
+Run a flight pattern and save the video automatically:
+
+```bash
+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
+```bash
+./scripts/record_simulation.sh --duration 30
+```
+
+---
+
+## 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).
+
+```bash
+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.