Crazyflie Isaac Framework (CIF)
Sep 1, 2026·
·
1 min read
Ömer Kurkutlu
Overview
The Crazyflie Isaac Framework (CIF) is an open-source robotics simulation framework built on NVIDIA Isaac Sim for Crazyflie nano-drone research. It brings configurable controllers, sensors, environments, and autonomous algorithms together in a single modular stack.
Key Features
- Configurable flight controllers and sensor models
- Customizable simulation environments
- Deep reinforcement learning training and evaluation
- Multi-drone experiments
- Benchmarking of autonomous navigation algorithms
- Sim-to-real experimentation with Crazyflie 2.x hardware
Project Status
Status: ✅ Open-sourced — developed as part of my PhD research at the University of Illinois Chicago.
NVIDIA Isaac Sim
Isaac Lab
Tiny Drones
Crazyflie
Deep Reinforcement Learning
Sim-to-Real
Multi-Agent Robotics
Authors
PhD Candidate in Electrical and Computer Engineering
I am a Ph.D. candidate in Electrical and Computer Engineering at the University of Illinois Chicago, advised by Dr. Arman Roohi. I specialize in robot learning, Physical AI, and autonomous systems. My research focuses on deep reinforcement learning, vision-language-action models, vision-based navigation, sim-to-real, and resource-constrained robotics, with hands-on experience in NVIDIA Isaac Sim/Isaac Lab, ROS/ROS2, and embedded AI.