Unmanned aerial vehicle (UAV) research requires the integration of cutting-edge technology into existing autopilot frameworks. This process can be arduous, requiring extensive resources, time, and detailed knowledge of the existing system. ROSplane is a lean, open-source fixed-wing autonomy stack built by researchers for researchers. It is designed to accelerate research by providing clearly defined interfaces with an easily modifiable framework. Built around ROS 2, ROSplane allows for rapid integration of low or high-level control, path planning, or estimation algorithms. A focus on lean, easily-understood code and extensive documentation lowers the barrier to entry for researchers. Recent developments to ROSplane improve its capacity to accelerate UAV research, including the transition from ROS 1 to ROS 2, enhanced estimation and control algorithms, increased modularity, and an improved aerodynamic modeling pipeline. This aerodynamic modeling pipeline significantly reduces the effort of transitioning from simulation to real-world testing without requiring costly system identification or computational fluid dynamics tools. ROSplane's architecture reduces the effort required to integrate new research tools and methods, expediting hardware experimentation.
@article{arxiv.2510.01041,
title = {ROSplane 2.0: A Fixed-Wing Autopilot for Research},
author = {Ian Reid and Joseph Ritchie and Jacob Moore and Brandon Sutherland and Gabe Snow and Phillip Tokumaru and Tim McLain},
journal= {arXiv preprint arXiv:2510.01041},
year = {2026}
}
Comments
Submitted to the 2026 International Conference on Unmanned Aerial Systems