# aerial-autonomy-stack -- a Faster-than-real-time, Autopilot-agnostic, ROS2 Framework to Simulate and Deploy Perception-based Drones

arXiv: https://arxiv.org/abs/2602.07264 · HTML: https://mlsanity.com/paper/2602.07264/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 34 references that are in the map.
- First posted on arXiv 6 Feb 2026.

## Builds on (most cited first, 16 of 16)

- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Way](https://mlsanity.com/paper/2209.15397/) (2022)
- [Neural Lander: Stable Drone Landing Control using Learned Dynamics](https://mlsanity.com/paper/1811.08027/) (2018)
- [Flightmare: A Flexible Quadrotor Simulator](https://mlsanity.com/paper/2009.00563/) (2020)
- [Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control](https://mlsanity.com/paper/2103.02142/) (2021)
- [Agilicious: Open-Source and Open-Hardware Agile Quadrotor for Vision-Based Flight](https://mlsanity.com/paper/2307.06100/) (2023)
- [The Reality Gap in Robotics: Challenges, Solutions, and Best Practices](https://mlsanity.com/paper/2510.20808/) (2025)
- [Fast, Autonomous Flight in GPS-Denied and Cluttered Environments](https://mlsanity.com/paper/1712.02052/) (2017)
- [Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots](https://mlsanity.com/paper/2503.01471/) (2025)
- [The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles](https://mlsanity.com/paper/2008.08050/) (2020)
- [RotorPy: A Python-based Multirotor Simulator with Aerodynamics for Education and Research](https://mlsanity.com/paper/2306.04485/) (2023)
- [Survey of Simulators for Aerial Robots: An Overview and In-Depth Systematic Comparisons](https://mlsanity.com/paper/2311.02296/) (2023)
- [XTDrone: A Customizable Multi-Rotor UAVs Simulation Platform](https://mlsanity.com/paper/2003.09700/) (2020)
- [Aerostack2: A Software Framework for Developing Multi-robot Aerial Systems](https://mlsanity.com/paper/2303.18237/) (2023)
- [What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities](https://mlsanity.com/paper/2308.10008/) (2023)
- [On Your Own: Pro-level Autonomous Drone Racing in Uninstrumented Arenas](https://mlsanity.com/paper/2510.13644/) (2025)

## Abstract (arXiv)

Unmanned aerial vehicles are rapidly transforming multiple applications, from agricultural and infrastructure monitoring to logistics and defense. Introducing greater autonomy to these systems can simultaneously make them more effective as well as reliable. Thus, the ability to rapidly engineer and deploy autonomous aerial systems has become of strategic importance. In the 2010s, a combination of high-performance compute, data, and open-source software led to the current deep learning and AI boom, unlocking decades of prior theoretical work. Robotics is on the cusp of a similar transformation. However, physical AI faces unique hurdles, often combined under the umbrella term "simulation-to-reality gap". These span from modeling shortcomings to the complexity of vertically integrating the highly heterogeneous hardware and software systems typically found in field robots. To address the latter, we introduce aerial-autonomy-stack, an open-source, end-to-end framework designed to streamline the pipeline from (GPU-accelerated) perception to (flight controller-based) action. Our stack allows the development of aerial autonomy using ROS2 and provides a common interface for two of the most popular autopilots: PX4 and ArduPilot. We show that it supports over 20x faster-than-real-time, end-to-end simulation of a complete development and deployment stack -- including edge compute and networking -- significantly compressing the build-test-release cycle of perception-based autonomy.