An ARGoS plug-in for the Crazyflie drone

TL;DR

The paper addresses the need for a high-fidelity Crazyflie model within ARGoS by introducing an open-source plug-in that faithfully simulates the drone’s body, LEDs, onboard camera, velocity and position PD controllers, a battery discharge curve, and Range and Bearing communications. The plug-in, built on the Spiri framework, is validated against real Crazyflie hardware, showing strong trajectory fidelity and accurate battery behavior, quantified with a cubic discharge fit and a Mean Squared Error of $MSE = 0.002114$. This work extends ARGoS capabilities for swarm robotics research, enabling hardware-in-the-loop validation and reproducible experiments. Overall, the plug-in provides researchers with a configurable, open-source tool to study Crazyflie-based swarms with realistic sensing, actuation, and energy constraints.

Abstract

We present a new plug-in for the ARGoS swarm robotic simulator to implement the Crazyflie drone, including its controllers, sensors, and some expansion decks. We have based our development on the former Spiri drone, upgrading the position controller, adding a new speed controller, LED ring, onboard camera, and battery discharge model. We have compared this new plug-in in terms of accuracy and efficiency with data obtained from real Crazyflie drones. All our experiments showed that the proposed plug-in worked well, presenting high levels of accuracy. We believe that this is an important contribution to robot simulations which will extend ARGoS capabilities through the use of our proposed, open-source plug-in.

Figures (9)

• Figure 1: The Crazyflie drone.
• Figure 2: Crazyflie 3D model showing the RGB LED included.
• Figure 3: The implemented onboard camera detecting two light sources.
• Figure 4: Calibration of the onboard camera. (50-degree aperture).
• Figure 5: Comparison of 2D drone trajectories for two Crazyflie drones (cf1 and cf2) and the ARGoS plug-in.