# RotorPy: A Python-based Multirotor Simulator with Aerodynamics for Education and Research

arXiv: https://arxiv.org/abs/2306.04485 · HTML: https://mlsanity.com/paper/2306.04485/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2023.

## Built on by (most cited first, 9 of 9)

- [Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems](https://mlsanity.com/paper/2401.04960/) (2024)
- [Agile Interception of a Flying Target using Competitive Reinforcement Learning](https://mlsanity.com/paper/2603.16279/) (2026)
- [Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX](https://mlsanity.com/paper/2606.01478/) (2026)
- [Proto-MPC: An Encoder-Prototype-Decoder Approach for Quadrotor Control in Challenging Winds](https://mlsanity.com/paper/2401.15508/) (2024)
- [Active Scout: Multi-Target Tracking Using Neural Radiance Fields in Dense Urban Environments](https://mlsanity.com/paper/2406.07431/) (2024)
- [Pareto Control Barrier Function for Inner Safe Set Maximization Under Input Constraints](https://mlsanity.com/paper/2410.04260/) (2024)
- [Maintaining Plasticity in Reinforcement Learning: A Cost-Aware Framework for Aerial Robot Control in Non-stationary Environments](https://mlsanity.com/paper/2503.00282/) (2025)
- [aerial-autonomy-stack -- a Faster-than-real-time, Autopilot-agnostic, ROS2 Framework to Simulate and Deploy Perception-based Drones](https://mlsanity.com/paper/2602.07264/) (2026)
- [Neurosim: A Fast Simulator for Neuromorphic Robot Perception](https://mlsanity.com/paper/2602.15018/) (2026)

## Abstract (arXiv)

Simulators play a critical role in aerial robotics both in and out of the classroom. We present RotorPy, a simulation environment written entirely in Python intentionally designed to be a lightweight and accessible tool for robotics students and researchers alike to probe concepts in estimation, planning, and control for aerial robots. RotorPy simulates the 6-DoF dynamics of a multirotor robot including aerodynamic wrenches, obstacles, actuator dynamics and saturation, realistic sensors, and wind models. This work describes the modeling choices for RotorPy, benchmark testing against real data, and a case study using the simulator to design and evaluate a model-based wind estimator.