Used in research

Flight lab

The Crazyflie is ideal for many areas of research


Flexible

The Crazyflie is the ideal tool for research in many areas, for instance control algorithms, swarms, path finding, agriculture or failure recovery. The platform is designed to be as flexible and versatile as possible to enable the user to explore the area of interest.

Extendable

Add new sensors or other hardware to support your needs, the expansion port supports a variety of interfaces and there is plenty of power in the processors for you to use. If you need more lifting capacity, use the BigQuad deck and move your application to a bigger frame, while still being able to develop it in the comfort of your lab.

Tools

The Crazyflie can be controlled from a number of programming languages and also integrates with tools and frameworks such as ROS or ZeroMQ. It works well with standard development tools to make your work a breeze.

Open

It is all open to allow you to change what you need to change, you will never be locked in by limited APIs or closed software. Never.

How the Crazyflie 2.0 is used by universities


Universities around the world are using the Crazyflie 2.0 in different types of research fields. Here we have collected guest blog posts from our blog to show some examples.

Crazyflie used by Carnegie Mellon University

“We use the Crazyflie platform to evaluate our algorithms because the hardware is robust and the user community has helped make firmware available on which we can base our own systems” -Ellen Cappo, researcher at Carnegie Mellon University.

Read about how the researchers at Carnegie Mellon University are using the Crazyflie 2.0 to test theory on real world systems. Towards persistent, adaptive multi-robot systems.

Crazyflie used by MIT

“The Crazyflie is easily obtainable, safe, and (we can certify ourselves) very robust. Moreover, since it is open-source and fully programmable, we were able to easily modify the Crazyflie to fit our needs.” -Brandon Araki, researcher at MIT.

In Multi-robot Path Planning for Flying-and-Driving Vehicles you can read about how the researchers at MIT are using the Crazyflie 2.0 to study the coordination of multiple robots.

Crazyflie used in research


Publications involving Crazyflie 2.0


  • “Planning and Control for Quadrotor Flight through Cluttered Environments”, B. Landry, Master’s thesis, Massachusetts Institute of Technology, USA, June 2015. PDF Video Code

  • “Mixed Reality for Robotics”, W. Hönig, C. Milanes, L. Scaria, T. Phan, M. Bolas, and N. Ayanian, IROS, 2015. PDF Video

  • “System Identification of the Crazyflie 2.0 Nano Quadrocopter”, J. Förster, Bachelor’s thesis, ETH Zürich, 2015. PDF

  • “Stippling with aerial robots”, B. Galea, E. Kia, N. Aird, and P. G. Kry, Computational Aesthetics / Expressive, 2016. PDF Video1 Video2

  • “Crazyswarm: A Large Nano-Quadcopter Swarm”, James A. Preiss, Wolfgang Honig, Gaurav S. Sukhatme and Nora Ayanian, in Proc. IEEE International Conference on Robotics and Automation, 2017. PDF Video

  • “A Hybrid Method for Online Trajectory Planning of Mobile Robots in Cluttered Environments”, Leobardo Campos-Macías, David Gómez-Gutiérrez, Rodrigo Aldana-López, Rafael de la Guardia and José I. Parra Vilchis, Multi-Agent Autonomous Systems - Intel Labs, 2017. PDF or PDF Video

  • “Target Following on Nano-sized UAV”, Jaskirat Singh, Master Thesis at ETH Zurich. PDF Video

Publications involving Crazyflie 1.0


  • “Development of a wireless video transfer system for remote control of a lightweight UAV”, J. Tosteberg and T. Axelsson, Master’s thesis, Linköping University, Sweden, June 2012. PDF

  • “Visual inertial control of a nano-quadrotor”, O. M. W. Dunkley, Master’s thesis, Technical University Munich, Germany, Sept. 2014. PDF Code

  • “Visual-inertial navigation for a camera-equipped 25g nano-quadrotor”, O. Dunkley, J. Engel, J. Sturm, and D. Cremers, in IROS2014 Aerial Open Source Robotics Workshop, 2014. PDF Video

  • “HoverBall : Augmented Sports with a Flying Ball”, Kei Nitta, Keita Higuchi and Jun Rekimoto, 5th International Conference on Augmented Human (AH 2014), 2014. PDF

  • “Perching Failure Detection and Recovery with Onboard Sensing”, Hao Jiang, Morgan T. Pope, Matthew A. Estrada, Bobby Edwards, Mark Cuson, Elliot W. Hawkes and Mark R. Cutkosky, IROS, 2015. PDF Video

  • “Nonlinear control strategies for quadrotors and CubeSats”, Giri Prashanth Subramanian, Master’s thesis, University of Illinois at Urbana-Champaign, USA, July 2015. PDF

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