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

2023/06/07 by Spencer Folk, Folk, Spencer, James Paulos +3 · 4 citations
Engineering · #Aerospace Engineering and Energy Systems #Aerospace and Aviation Technology #FOS: Computer and information sciences #Inertial Sensor and Navigation #Robotics (cs.RO)

paper · pdf · doi:10.48550/arxiv.2306.04485

openalex publication_date 2023/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

Cited by

• TACO: Trajectory-Aware Controller Optimization for Quadrotors
• A Simulation Evaluation Suite for Robust Adaptive Quadcopter Control
• Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis
• Vectorized Sparse Second-Order Forward Automatic Differentiation for Optimal Control Direct Methods

Related

• Advanced Autonomy on a Low-Cost Educational Drone Platform
• PythonRobotics: a Python code collection of robotics algorithms
• Pegasus Simulator: An Isaac Sim Framework for Multiple Aerial Vehicles Simulation
• UAIbot: Beginner-friendly web-based simulator for interactive robotics learning and research
• Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots