Hello ROS 2 and robotics simulation community,
I would like to introduce FastSwarmSim, an open-source, lightweight multi-UAV simulator for PX4-compatible vehicles:
- GitHub: GitHub - shupx/FastSwarmSim: lightweight multi-drone simulator · GitHub
- Documentation: FastSwarmSim Documentation
FastSwarmSim is designed for multi-robot algorithm development and repeatable simulation-time experiments. It combines a trimmed PX4 runtime, MAVROS-compatible ROS interfaces, RViz visualization, local LiDAR point-cloud rendering, and a conservative lock-step simulation clock.
A key feature: lock-step simulation time
FastSwarmSim publishes simulation time through ROS 2 /clock and advances the simulation in lock-step. This makes simulation progress explicit and reproducible instead of being tied directly to wall-clock speed.
With a small adaptation, a ROS node can participate in this timing model: use ROS time, respond to /clock, and advance its algorithm or publish outputs according to the simulation-time cycle. This allows existing ROS nodes to be integrated into lock-step experiments without redesigning the whole system. Nodes that are not adapted can still run normally, but they will not provide the same deterministic lock-step behavior.
The practical result is that the same experiment can be run faster than real time when the workload allows it, while retaining a consistent simulation-time reference across PX4, ROS 2 nodes, sensors, and controllers. This is useful for high-volume algorithm testing, repeatable multi-UAV experiments, accelerated parameter sweeps, and timing-sensitive coordination studies.
Current capabilities
- PX4-compatible multi-rotor simulation;
- single- and multi-vehicle launch workflows;
- ROS 2 and MAVROS-compatible interfaces;
- namespace-based multi-vehicle operation;
- RViz visualization;
- local LiDAR point-cloud simulation;
- ROS 2 command-line tools, including map generation;
- keyboard control for interactive vehicle operation;
- documentation hosted with GitHub Pages.
On a desktop-class computer, the documentation reports operation up to approximately 100x real time for a single vehicle with LiDAR simulation disabled, with lower but still accelerated rates as the vehicle count increases.
The project is still evolving, and feedback, use cases, and contributions are welcome.
Best regards,
Peixuan Shu, Beihang University, China
Email: shupeixuan@qq.com