gym-pybullet-drones
Active·★ 2.1k·Updated 2026-07-11
★ Trending
gym-pybullet-drones is a minimalist refactoring of its original repository, providing a Gym environment for simulating multi-agent quadcopter control. It is designed for compatibility with Gymnasium, Stable Baselines3 2.0, and various flight firmwares for hardware-in-the-loop simulation.
gym-pybullet-drones is currently grouped under LLM Infra, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Gymnasium and Stable Baselines3 2.0 compatibility and Developing and evaluating PID controllers for quadcopter flight. It also shows measurable community traction with 2.1k GitHub stars.
#Reinforcement Learning#Quadcopters#Robotics Simulation#PyBullet#Gymnasium
01
Features
01Gymnasium and Stable Baselines3 2.0 compatibility
02Betaflight/Crazyflie firmware SITL integration
03PID control examples for drone navigation
04Reinforcement learning (PPO) for single and multi-agent quadcopter control
05Multiplatform support for Ubuntu and macOS
02
Why choose it
+Gymnasium and Stable Baselines3 2.0 compatibility
+Developing and evaluating PID controllers for quadcopter flight
+Covers 5 supported environments or platforms, which is helpful for broader deployment needs.
+The latest recorded update is 2026-07-11, which suggests the project is still actively maintained.
03
Trade-offs
!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04
Compatibility
Gymnasium
Supported
Verified via docs
Stable Baselines3
Supported
Verified via docs
Betaflight
SITL Integration
Verified via docs
Crazyflie-firmware
SITL Integration
Verified via docs
PyBullet
Native
Verified via docs
05
Quick start
1
$ pip3 install -e .
06
Use cases
↳Developing and evaluating PID controllers for quadcopter flight
↳Training single and multi-agent reinforcement learning policies for drone control tasks
↳Integrating with real flight firmwares like Betaflight for Software-in-the-Loop (SITL) simulations
07
How it compares
≈gym-pybullet-drones sits in the LLM Infra category, so it makes more sense to evaluate it alongside tools like MetaGPT instead of in isolation.
≈If your main need is closer to "Developing and evaluating PID controllers for quadcopter flight", that use case is a better lens for comparison than broad feature checklists alone.
≈gym-pybullet-drones's licensing and community traction are both easier to judge in category context.
08
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