This code accompanies the work in the ICRA 2024 paper "CrazySim: A Software-in-the-Loop Simulator for the Crazyflie Nano Quadrotor" [1]. CrazySim is a simulator platform that runs Crazyflie firmware in a simulation state on a desktop machine with integrated communication with Gazebo sensors and physics engine. The simulated Crazyflie firmware is intended to communicate with a custom Crazyflie Python library (CFLib) provided in this code. This enables simulating the behavior of CFLib scripts that are intended to control single or multiple Crazyflies in a real hardware demonstration. With CFLib communication capabilities, users can choose to use CrazySwarm2 with CFLib as the backend for a ROS 2 interface with the simulator.

[1] C. Llanes, Z. Kakish, K. Williams, and S. Coogan, “CrazySim: A Software-in-the-Loop Simulator for the Crazyflie Nano Quadrotor,” To appear in 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024.

@INPROCEEDINGS{LlanesICRA2024,
  author={Llanes, Christian and Kakish, Zahi and Williams, Kyle and Coogan, Samuel},
  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)}, 
  title={CrazySim: A Software-in-the-Loop Simulator for the Crazyflie Nano Quadrotor}, 
  year={2024},
  volume={},
  number={},
  pages={12248-12254},
  keywords={Sockets;Prediction algorithms;Hardware;Robustness;Sensors;Trajectory;Task analysis},
  doi={10.1109/ICRA57147.2024.10610906}}

This simulator is currently only supported on Ubuntu systems with at least 20.04. This is primarily a requirement from Gazebo Sim. The simulator was built, tested, and verified on 22.04 with Gazebo Garden.

To install this repository use the recursive command as shown below for HTTPS:

git clone https://github.com/gtfactslab/CrazySim.git --recursive

The SETUPTOOLS_SCM_PRETEND_VERSION variable is needed because the submodule does not contain the git tags required by setuptools_scm to determine the package version automatically.

cd crazyflie-lib-python
SETUPTOOLS_SCM_PRETEND_VERSION=0.1.31 pip install -e .

If you want to test a single Crazyflie with crazyflie-clients-python for SITL, then run the following commands in your terminal. If pip reinstalls cflib, then you may have to remove it and install from source above.

We have verified success with commit d649b66.

git clone https://github.com/bitcraze/crazyflie-clients-python
cd crazyflie-clients-python
pip install -e .

[WARNING] This is a modified version of the crazyflie-firmware for software-in-the-loop. At this time do not use this firmware for your hardware. SITL integration with Kbuild is being developed for cross-platform building.

The installation instructions and usage are referenced in the documentation file.

Run the following commands to install dependencies.

sudo apt install cmake build-essential
pip install Jinja2

First install Gazebo Garden from https://gazebosim.org/docs/garden/install_ubuntu

Run the command to build the firmware and Gazebo plugins.

cd crazyflie-firmware
mkdir -p sitl_make/build && cd $_
cmake ..
make all

Open a terminal and run

cd crazyflie-firmware

We can then run the firmware instance and spawn the models with Gazebo using a launch script. All launch scripts require a model argument -m. All currently implemented models are tabulated below.

bash tools/crazyflie-simulation/simulator_files/gazebo/launch/sitl_singleagent.sh -m crazyflie -x 0 -y 0

bash tools/crazyflie-simulation/simulator_files/gazebo/launch/sitl_multiagent_square.sh -n 8 -m crazyflie

bash tools/crazyflie-simulation/simulator_files/gazebo/launch/sitl_multiagent_text.sh -m crazyflie

Now you can run any CFLib Python script with URI udp://0.0.0.0:19850. For drone swarms increment the port for each additional drone.

You can also test a single crazyflie using the custom client if you installed it from the crazyflie-clients-python section.

First start up the custom client.

cfclient

Click on the SITL checkbox, scan, and connect. Once it's connected you can take off and fly using the command based flight controls.

One use case for simulating a crazyflie with the client is real time PID tuning. If you created a custom crazyflie with larger batteries, multiple decks, and upgraded motors, then it would be useful to tune the PIDs in a simulator platform before tuning live on hardware. An example of real time PID tuning is shown below.

This section follows the setup of Crazyswarm2 with CrazySim. We provide an example workflow of launching 4 Crazyflies using CrazySim and connect them to Crazyswarm2.

1. Make sure you have ROS 2 Humble.

2. Build the Crazyswarm2 workspace provided as a submodule.

cd crazyswarm2_ws
colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release
source install/setup.bash

The crazyswarm2 configuration files can be found in

crazyswarm2_ws/src/crazyswarm2/crazyflie/config/

The crazyflies.yaml describes the robots currently being used. If a robot is not in the simulator or hardware, then it can be disabled by setting the enabled parameter to false. A more detailed description for crazyswarm2 configurations can be found here.

For the following demo make the following adjustments to the robots and robot_types in crazyflies.yaml.

robots:
  cf_1:
      enabled: true
      uri: udp://0.0.0.0:19850
      initial_position: [0.0, 0.0, 0.0]
      type: cf_sim

  cf_2:
    enabled: true
    uri: udp://0.0.0.0:19851
    initial_position: [1.0, 0.0, 0.0]
    type: cf_sim

  cf_3:
    enabled: true
    uri: udp://0.0.0.0:19852
    initial_position: [0.0, 1.0, 0.0]
    type: cf_sim 

  cf_4:
    enabled: true
    uri: udp://0.0.0.0:19853
    initial_position: [1.0, 1.0, 0.0]
    type: cf_sim

robot_types:
  cf_sim:
    motion_capture:
      tracking: "vendor"
    big_quad: false
    firmware_logging:
      enabled: true
      default_topics:
        pose:
          frequency: 10

Start up the firmware with any of the 3 launch script options. Below we demonstrate 4 Crazyflies in a square formation.

bash tools/crazyflie-simulation/simulator_files/gazebo/launch/sitl_multiagent_square.sh -n 4 -m crazyflie

Make sure that cf_1, cf_2, cf_3, and cf_4 are enabled in the CrazySwarm2 configuration YAML file. Launch the Crazyswarm2 services with the CFLib backend:

ros2 launch crazyflie launch.py backend:=cflib

Or with the C++ backend:

ros2 launch crazyflie launch.py backend:=cpp

The model predictive control example from [1] has been moved to a separate repository.