You might already be familiar with the Crazyflie’s presence in numerous publications across various research fields. However, in this blog post, we’ll return to the basics and showcase some robotics concepts that can be taught using our platform.
The Crazyflie has already found its way into several classrooms such as the “Introduction to Robotics” in the Mechanical & Aerospace Engineering Department at Princeton University, the “Introduction to Control of Unmanned Aerial Vehicles” at UC Berkeley and the “Embedded control systems” at Chalmers University of Technology.
Whether you’re designing a robotics course for undergraduates or developing advanced labs for graduate students, here’s some fields where the Crazyflie can help your students grasp the fundamentals of modern robotics.
Basic Drone Principles
How does the quadcopter generate enough thrust? In which direction should the motors spin? How does the shape of a propeller affect performance?
As an introduction to drones and specifically quadcopters, students can explore these basic principles behind how they work. Then, by flying them, they can better understand the three axes of motion, roll, pitch and yaw and even find out their limitations, such as the ground effect.
Control Systems
What is the difference between controllers? How does a different controller tuning affect performance? How does an estimator work? What types of commands can be sent to a drone?
The Crazyflie platform offers a rich “playground” for exploring the stabilization process from sensor acquisition to motor control, that we often call “stabilizer module“. This includes a variety of controllers, estimators and commanders that can be modified to visualize results in the real world. Also, with the firmware being open-source and modular, it is relatively easy to build your own controller or estimator and integrate it to the platform.
Localization
How can a drone know its position and orientation in 3D space? What is the difference between a local and a global positioning system?
With a wide variety of deck sensors and positioning systems, students can find ways to control the Crazyflie through relative or absolute position/attitude commands. The different sensing methods used in these systems are also interesting to explore – for example, IR signals from the Lighthouse Positioning System, UWB radio from the Loco Positioning System, or optical flow data from the Flow deck v2.
Autonomous Navigation
How could the Crazyflie perform a collision-free trajectory? What is the most efficient way of flying from point A to point B?
In the field of autonomous navigation, the Crazyflie can be treated like any other moving robot by applying existing path planning algorithms or testing newly developed ones. Environment-aware problems are always exciting to work on and the Multi-ranger deck makes them feasible.
Swarm Robotics
What happens when you add another Crazyflie to your setup? How could multiple Crazyflies operate in a swarm? How could you make sure that they won’t collide? What is the difference between a centralized and a decentralized swarm?
Scaling a system up is always challenging but also fascinating. The examples provided in our Python library help you get a swarm in the air, but it’s up to you and your students to explore how the Crazyflies should coordinate and cooperate.
Small Drone, Big Educational Impact
The Crazyflie ecosystem is a fully capable robotics lab in the palm of your hand. Its flexibility, safety, and robust API support make it ideal for hands-on learning in a wide variety of robotics fields. Integrating the Crazyflie into a university robotics curriculum, gives students the chance to explore, test, fail, and fly their way to mastery.