gym-pybullet-drones
- Software
- Drones and boats
- Simulator
A minimalist Gymnasium-compatible quadcopter simulation environment built on PyBullet physics, for control and reinforcement learning research with multiple drones.
Made by Learning Systems and Robotics Lab (LSY), Germany (checked on github.com/learnsyslab (opens in a new tab)).
Source on GitHub: github.com/learnsyslab/gym-pybullet-drones (opens in a new tab). Facts read at commit 0156312 (opens in a new tab).
Licenses
- Code
- MIT (opens in a new tab)
Read by Robotheca from LICENSE (opens in a new tab) (MIT) at commit 0156312 (opens in a new tab), on 16 Oct 2026.
- Commercial use
- Yes
What it does
- Provides a refactored, Gymnasium- and stable-baselines3-compatible drone environment built on PyBullet.
- Includes PID and velocity control examples, plus an MRAC controller example.
- Offers a downwash effect example showing aerodynamic interaction between drones.
- Supports single-agent and multi-agent reinforcement learning examples using PPO from stable-baselines3.
- Includes a Betaflight SITL example for running simulated flight controllers, one per drone.
- Ships a pytest test suite that can be run from the repository root.
Written by Robotheca from the project's README (opens in a new tab) at commit 0156312.
Getting started
- Difficulty
- Intermediate
- Hardware it needs, as the project states it
- Tested on Intel x64 with Ubuntu 24.04 and on Apple Silicon with macOS 26. The Betaflight SITL example is Ubuntu only.
- How to start
- The project's website (opens in a new tab)
Maintenance
- Status
- Active: a commit in the last 90 days
- Newest commit
- 12 Oct 2026 on main
- Latest release
- v1.0.0 (9 Mar 2021)
Checked on GitHub on 16 Oct 2026.
Links
Robots on Robotheca that use it
No robot on Robotheca is linked to it yet. Links come from a robot's robot.yaml, from its dependency files read as text, or from Robotheca's editors.
Robotheca lists software as a reference: nothing is hosted or run here, and every fact links to where it was read.