GamaFlyware

An Open-Source Simulation Platform for Autonomous Vision-Guided UAV Missions.

GamaFlyware.Showcase.mp4

About the System

The platform can support several features:

• Navigating areas via Python code
• Autonomous landing in pads
• Simulatenous Localization and Mapping (SLAM)
• Surveying indoor or outdoor environments
• SLAM point cloud processing
• Live plotting of flight data
• Missions in several maps

The system is implemented in a DockerHub image to be run on a Desktop, including all the tools, GUI and instalations. Should be simple to start using.

You can also read my Software Engineering B.A. Capstone Project about GamaFlyware.

Prerequisites

Make sure you have the following installed on your Linux Ubuntu 22.04 host:

• VSCode and Contaier extension

To install VSCode and the Container extension:

sudo snap install --classic code

After installing VSCode, launch it and open the Extensions Marketplace. Search for and install the Dev Containers extension (by Microsoft).

• Docker & Docker Compose plugin

sudo snap install --classic code

Then, open VSCode and install the Dev Containers extension from the Extensions Marketplace.

sudo apt-get update
sudo apt-get install docker.io docker-compose-plugin -y

• NVIDIA drivers

To enable GPU acceleration with Docker Compose, download and install the latest NVIDIA drivers for your GPU from the official NVIDIA website. After installing the drivers, also install the NVIDIA Container Toolkit:

sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker

Note: Proper driver installation is required for GPU passthrough and CUDA support inside containers.

Getting Started

1. Clone this repository:

git clone https://github.com/RenatoBrittoAraujo/GamaFlyware

Pulling the Docker Image

This prebuilt image (~40 GB) contains PX4-Autopilot, Gazebo Garden, ROS 2 Humble, and all dependencies:

sudo docker pull renatobrittoaraujo/gamaflyware:1

Note: Download may take several minutes.

Launching the Container

1. Remove or rename any existing container named gamaflyware.
2. Edit docker-compose.yml if you need to change RAM/CPU limits or adapt GPU settings for non-Ubuntu hosts.
3. Start in detached mode:

sudo docker compose up -d

Allowing GUI Windows from Docker

On the host, permit the container to open windows (Gazebo, OpenCV GUIs, etc.):

xhost local:docker

Running Your Code

Option 1: Launch all terminals with VSCode extension

In VSCode, type Ctrl+Shift+P and select Dev Containers: Restore and Reopen in Container. This will automatically restore all recommended terminals for your workspace.

Option 2: Manual Steps

1. Open a shell in the container

sudo docker exec -it gamaflyware bash

2. Start PX4 SITL + Gazebo

cd PX4-Autopilot
source /opt/ros/humble/setup.bash
make px4_sitl gz_x500

3. Build & run your ROS 2 package

cd ws
source /opt/ros/humble/setup.bash
source install/setup.bash
colcon build --packages-select mission
ros2 run mission land

4. Launch XRCE or MAVROS agent

• MAVROS:

source /opt/ros/humble/setup.bash
ros2 run mavros mavros_node --ros-args -p fcu_url:=udp://@127.0.0.1:14545

5. Run QGroundControl

./QGroundControl.AppImage

6. Bridge Gazebo camera to ROS

cd ws
source /opt/ros/humble/setup.bash
source install/setup.bash
ros2 run ros_gz_image image_bridge /camera

Troubleshooting & Tips

• MAVROS “broadcast request timeout” warning:

1. Install ss inside container:

sudo apt-get update && sudo apt-get install -y iproute2

2. List UDP ports:

ss -uln

3. Rerun MAVROS with correct port:

ros2 run mavros mavros_node --ros-args -p fcu_url:=udp://:14540@127.0.0.1:<YOUR_PORT>

• Changing Gazebo world/model paths:

Use models folder gz to insert your new models.