Open Source Linux Drone Software

PX4 is used in a wide range of use-cases, from consumer drones to industrial applications. It is also the leading research platform for drones and has been successfully applied to underwater vehicles and boats. PX4 provides a standard to deliver drone hardware support and software stack, allowing an ecosystem to build and maintain hardware and software in a scalable way. Drone development is complicated, and how to get started can be daunting and hard to navigate. These tutorials and resources provide a walkthrough of the basics of PX4. PX4 is highly portable, OS-independent and supports Linux, NuttX and MacOS out of the box. The PX4 User Guide explains how to assemble supported vehicles and fly drones with PX4. See the forum and chat if you need help!

The PS-Drone-API is a full featured SDK, written in and for Python, for Parrot's AR.Drone 2.0. It was designed to be easy to learn, but it offers the full set of the possibilities of the AR.Drone 2.0, including Sensor-Data (aka NavData), Configuration and full Video-support. The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for professional purposes can be satisfied. PS-Drone comes with a tutorial, explaining its most important commands and the drone's most important sensor values. The examples are easy to understand for people with little programming experience. A full list of commands and a description of all sensor data is available in a detailed documentation. It took several months to create PS-Drone, so it would be nice to get some donations for further development (e.g. Parrot's Bebop) and as a appreciation.

GAAS (Generalized Autonomy Aviation System) is an open source software platform for autonomous drones and VTOLs. GAAS was built to provide a common infrastructure for computer-vision based drone intelligence. In the long term, GAAS aims to accelerate the coming of autonomous VTOLs. Being a BSD-licensed product, GAAS makes it easy for enterprises, researches, and drone enthusiasts to modify the code to suit specific use cases. Our long-term vision is to implement GAAS in autonomous passenger carrying VTOLs (or "flying cars"). The first step of this vision is to make Unmanned Aerial Vehicles truly "unmanned", and thus make drones ubiquitous. We currently support manned and unmanned multi-rotor drones and helicopters. Our next step is to support VTOLs and eVTOLs.

The AR Drone is a quadrotor helicopter sold by Parrot. Parrot sells the drone as a toy controlled via a wireless device such as Ipods, Ipads, or Android based devices. Parrot advertises the toy as an advance in gaming because the control devices will project a virtual reality allowing users to play with their physical drone with an enhanced version on their controller where bullets or hot air balloons must be avoided in the virtual world. KIPR, KISS Institute for Practical Robotics is an organization that facilitates the learning of robotics programming in middle and high school students to peak an interest in computer science. To do this they hold competitions around the world called botball where students program autonomous land robots to perform various sets of tasks. KIPR, now wants to expand and leave the ground by integrating flying robots (the AR Drone) into the tasks for added interest, fun, and challenge for students.

The DTC (Drone Traffic Control) project for air traffic drones. It also utilizes DGPS for accurate position measurement of the drones.

OpenReco is an open-source photogrammetry and reality-capture platform designed to turn photographs into accurate 3D models, dense point clouds, textured meshes, DEMs, and orthomosaics. Built for researchers, drone operators, surveyors, developers, hobbyists, and digital artists, OpenReco aims to provide a transparent and extensible alternative to proprietary photogrammetry software. The project focuses on ease of use, performance, and reproducible workflows while embracing the open-source ecosystem. OpenReco supports image alignment, camera calibration, sparse and dense reconstruction, mesh generation, texturing, and export to common formats. Whether you're reconstructing archaeological sites, creating digital twins, generating terrain models, or building assets for games and visualization, OpenReco provides a powerful foundation without licensing restrictions.

"Drone WayPointer" is a ROS package that provides a UI to allow for remote control of the Parrot AR Drone 2.0. It is developed in C++ with qt-ros and the Qt4 Development FrameWork. It is designed to work with the ROS - Fuerte and it uses the the ardrone_autonomy driver (Fuerte-devel Branch). It has so far only been tested on the tum_simulator and not on the actual drone. The main functionalities it provides is camera streams of front or bottom cameras of the drone, button and slider control of the drone XYZ velocities, control using waypoints and waypoint commands, pose estimation using simple dead-reckoning and measurement and image recording functionalities.

pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers.

ar-drone is a Node.js client library for controlling Parrot AR.Drone quadcopters over their network protocol. It provides a high-level API for common flight operations such as takeoff, landing, altitude changes, rotation, directional movement, and hovering. Programs can receive navigation telemetry including flight state, altitude, and other sensor data. Camera output can be accessed as raw video streams or converted into PNG frames through FFmpeg. The library also exposes predefined flight animations, LED sequences, configuration commands, and emergency recovery controls. An interactive REPL lets developers experiment with drone commands directly before building autonomous scripts. Lower-level UDP controls are available for applications that need closer access to the drone's command protocol.

Gym-PyBullet-Drones is an open-source Gym-compatible environment for training and evaluating reinforcement learning agents on drone control and swarm robotics tasks. It leverages the PyBullet physics engine to simulate quadrotors and provides a platform for studying control, navigation, and coordination of single and multiple drones in 3D space.