Open Source BSD Drone Software

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.

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.